Suppose you have a matrix of time series, where each column is a time series.
Now, suppose you take second differences of this matrix, (so the data is stationary), using this code:
var_train_data <- diff(var_train, differences = 2)
and then you estimate this model:
var_1 <- VAR(y=var_train_data, lag=9, type="const")
Recall that this function VARcomes from vars package.
How can you plot the original data and the fitted(var_1) data? Is there a function to return the fitted data from the VAR to "level"?
I want to do this but with a VAR.
Thanks in advance!!
Here is the data:
> dput(var_train)
structure(c(8.59225428063812, 8.61632381521795, 8.48941975098913,
8.42616336163893, 8.4656261753598, 8.49981580266834, 8.50658473928686,
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9.43080717829243, 9.48542815127549, 9.80315392429245, 9.46220102483428,
9.49195605787191, 9.58345398545618, 9.63034810064769, 9.62459170291441,
9.97734143922148, 7.7599692507259, 10.24019393111, 9.83720243907435,
9.76324132919314, 9.80448476069629, 10.1429407688952, 9.78954063027604,
9.81148978580127, 9.90999022870695, 9.88337955430856, 9.86638017850479,
10.3500614614058, 8.04569598345531, 10.5137723520267, 10.0317143144973,
10.0016019420988, 10.0649053768744, 10.4518094727319, 10.0925802568863,
10.1154740580661, 10.2417047261218, 10.2102565428829, 9.95096958506337,
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10.213399969191, 10.4108390826055, 10.7497332163144, 10.3922428157884,
10.3629994803926, 10.5490843518049, 10.5299430900147, 10.5342652815607,
10.903442654213, 10.523826123055, 9.94829558655345, 11.0676534061714,
10.7289541973848, 10.7146558087789, 11.1095150342409, 10.7975434766392,
10.8030323275495, 10.9150557366667, 10.8468764795822, 10.1911966896029,
11.575751749895, 10.8395599835383, 10.9068704738973, 11.155501263489,
11.0291969763111, 11.0962769537602, 11.4469279398172, 11.0612218040278,
11.1062426423224, 11.2517538845846, 11.2333784859651, 10.9841022587667,
11.7991470802475, 11.2598050882812, 11.254649905487, 11.4720292631746,
11.3598860229692, 11.4170427738813, 11.766391720184, 11.4134853828265,
11.4410605118049, 11.5576389232754, 11.5626475736127, 11.5282047555652,
11.9147793383982, 11.4669389639854, 11.5920019692809, 11.7656439584139,
11.5489709584581, 11.6145933534541, 12.0526884789762, 11.5721225093198,
11.5785294086931, 11.9478679038354, 11.7577088515946, 11.644026901156,
12.282699606583, 11.6893399093708, 11.7081194573217, 12.0745898194066,
11.8513909555241, 12.0120697218447, 12.3777829279197, 11.9427908749701,
11.9852440709239, 12.2849763358503, 12.1610242572971, 12.2863478497246,
12.6987948609176, 8.87626014701704, 8.75781187913873, 8.79677757108755,
8.86048921162718, 9.42285091166665, 9.15587149508903, 9.07157541184028,
9.04422296009634, 8.98415367463587, 8.99264229713128, 8.99995926865439,
8.98630888588454, 9.08279027699937, 9.01801415653217, 9.03092644682495,
9.13585333120665, 9.3964555249613, 9.31056129804753, 9.21149824677136,
9.23582853002755, 9.19896921092407, 9.1993094115266, 9.22157244245253,
9.33255711303986, 9.32050974348142, 9.25734511507957, 9.25346237744606,
9.21161756310925, 9.57206242922829, 9.53477519401849, 9.44848135105606,
9.4736925056348, 9.45353618677624, 9.50006144281617, 9.53134203318552,
9.55522920290037, 9.58433205464551, 9.49975115996635, 9.54279990568933,
9.4939629665153, 9.8456088597159, 9.80015328006924, 9.76821638323259,
9.79109456264224, 9.72522763542793, 9.77851709053319, 9.8204171003855,
9.88434452165958, 9.98640258678757, 9.88349657543331, 9.78072105929449,
9.91545274615568, 10.0965440644382, 10.069889220858, 10.1071834236742,
10.0960053864793, 10.0816170924409, 10.0972659507375, 9.98273573064832,
10.0707648293296, 10.0903422031634, 10.0334967498009, 9.988071454218,
10.0452755646408, 10.214325988114, 10.1943936821307, 10.20408926276,
10.1374653682538, 10.1747246925649, 10.1817608649851, 10.1694093867828,
10.2457147073325, 10.2759167729448, 10.2174707468632, 10.2579653028569,
10.3132625062745, 10.5801172770154, 10.5266233798438, 10.5287486381328,
10.4503144592933, 10.481479184849, 10.4934241207427, 10.502542901769,
10.5494285881606, 10.6156346275554, 10.5119074689424, 10.5311093136153,
10.5900727521127, 10.832499150024, 10.7930060469324, 10.775718578877,
10.7531531154054, 10.773311204382, 10.7696395290979, 10.7637570976447,
10.7977938807946, 10.8750990746633, 10.763894326936, 10.7864939948099,
10.8084313558315, 11.0190608163543, 10.9799244653747, 11.0238093735289,
11.0096646409103, 10.9573562063908, 11.0042746906925, 11.0131160377438,
11.0384446615171, 11.0925921149442, 11.016788345678, 11.0067286524726,
11.1218140056974, 11.2613143806394, 11.2211796761646, 11.2935015874788,
11.2367103049134, 11.1817094995799, 11.2157604633905, 11.2061686914688,
11.2392748154291, 11.4109721102435, 11.3043371225574, 11.2735248395737,
11.4375261360429, 11.5623874976603, 11.5247175044255, 11.5814242903823,
11.5093986724378, 11.5000330452891, 11.5579600619228, 11.5311240131655,
11.5954153362326, 11.6738399129326, 11.57644340322, 11.5655204319799,
11.6321174901907, 11.8360148309349, 11.8553639635506, 11.8913520673329,
11.7944527780615, 11.770991474902, 11.8087026529826, 11.7713523360005,
11.884723151518, 11.9993814545919, 11.8115717892501, 11.8332855179777,
11.9237740730483, 12.0455787827743, 12.0702342014546, 12.1012197983564,
12.0183149296719, 12.0336059065465, 12.0269239230024, 12.1132590047525,
12.5264959691571, 12.2615706812812, 12.0565371292502, 12.2657313524817,
12.1439258858968, 12.2359003050756, 12.3309092088311, 12.3771893569204,
12.3071632432092, 12.3196939443778, 12.3000789109455, 12.321469532421,
12.3683550017493, 12.4759510736235, 12.3701719620075, 12.3835321964786,
12.372549767611, 12.5961565138223, 12.6077080727407, 12.5909743980745,
12.5893548765137, 12.5974984744602, 12.6523879936874, 12.6119355657399,
12.6758307918205, 12.8047085707425, 12.7095434517684, 12.7003715885686,
12.7865053255695, 13.0041421782442, 13.0268258741114, 13.0190226032443,
13.0357037893755, 12.9527882182394, 13.0084592868531, 13.0707965999479,
13.1069788399601, 1.04885832686158, 1.06016074629379, 1.0517956106758,
1.02907998600003, 1.05054370620123, 1.07261670636915, 1.0706491823234,
1.0851355199628, 1.08488055975672, 1.08085233559646, 1.081489249884,
1.08587205516048, 1.07249155362154, 1.05497731364761, 1.05675866316574,
1.06428371643968, 1.06065865122313, 1.05621234529568, 1.05339905298902,
1.05787030302435, 1.0658034000068, 1.08707776713932, 1.08626056161822,
1.10238697375394, 1.11390088086972, 1.12120513732074, 1.11937921359653,
1.10341241626668, 1.1156190247407, 1.12376155972358, 1.12411603174635,
1.12183475077377, 1.12994175229071, 1.12956170931204, 1.12199732095331,
1.11645064755987, 1.12481242467782, 1.13066151473637, 1.13028712061827,
1.12694056065497, 1.12382226475179, 1.12352013167586, 1.13391069257413,
1.14763982976838, 1.14481816405703, 1.14852949174863, 1.14182560351963,
1.14086563926171, 1.14491904045717, 1.14897189333479, 1.14616964486707,
1.15074750127031, 1.14681353487065, 1.11151754535415, 1.10497749493861,
1.10963378437214, 1.12415745716768, 1.17507535290893, 1.20285968503846,
1.22784769136553, 1.23940795216891, 1.254741010879, 1.29442450660416,
1.30428779451896, 1.31314618462517, 1.32544236970695, 1.33728107423435,
1.34408499591568, 1.34199331033196, 1.34027541040719, 1.33616830504407,
1.33360421057602, 1.33332422301893, 1.34717794252774, 1.3502492092262,
1.35168291803248, 1.35827816606688, 1.36772644852242, 1.36755741578293,
1.36926148542701, 1.37264481021763, 1.37322962601678, 1.37643913938007,
1.37906284181634, 1.37644362054554, 1.38911039237937, 1.39412557349575,
1.40094895608589, 1.40630864159528, 1.40823485306921, 1.4138446752069,
1.42340582796496, 1.43641264727375, 1.43605231080207, 1.44839810240334,
1.45451041581127, 1.46166006472498, 1.46774816064695, 1.46930608347752,
1.47885183796249, 1.49059366171423, 1.49849145403671, 1.51209667142067,
1.5250141727637, 1.5392257264567, 1.55144303632514, 1.56488453313021,
1.58308777691125, 1.59737589266492, 1.60896279958586, 1.62553339664661,
1.63594174408691, 1.65233080464302, 1.67114336171075, 1.6897476078746,
1.71673790971729, 1.74453973794979, 1.76317526009814, 1.79187692264759,
1.84186982937622, 1.9460629324144, 2.05986108970089, 2.06767436493269,
2.0783176148561, 2.08271855277262, 2.09358626977224, 2.09674958523685,
2.11582742548029, 2.12810020369675, 2.13596929171732, 2.13972610568317,
2.14456803530813, 2.15013985201827, 2.16007349878874, 2.17165498940627,
2.18057666565755, 2.19162746118342, 2.20308765886345, 2.21304799942168,
2.22367586966847, 2.23629862083737, 2.24751866055731, 2.26100586740225,
2.40972893063106, 2.60366275683037, 2.68572993101095, 2.70501080420283,
2.6676315643757, 2.6479269687206, 2.64641010174172, 2.69966594490103,
2.69665303568271, 2.71396750774502, 2.71900427132191, 2.72876269360869,
2.76276620421252, 2.76620189252239, 2.74632816231219, 2.74196673817286,
2.72905831066292, 2.75190757584346, 2.77801573354251, 2.84089580821293,
2.85681823660541, 2.84754572013613, 2.85858396073969, 2.86184353545653,
2.86958309986952, 2.94279115543111, 2.98631808884879, 3.00648449252989,
3.00620698598987, 3.15207693676406, 3.27614511764022, 3.32011714920345,
3.39367422894347, 3.64822360464499, 3.61835354049394, 3.59374251055335,
3.63237359915986, 3.62209957896007, 3.64554153297999, 3.71611226971083,
3.76031231050606, 3.80307769833913, 3.77959145461296, 3.74772344909971,
3.95072671083008, 4.03652777624058, 4.06630193640976, 4.08838169421096,
4.09074775372752), .Dim = c(192L, 7L), .Dimnames = list(NULL,
c("EMBI+", "M2 (pesos)", "Commodity Price index", "emae",
"gasto programas SS", "recursos tributarios", "ex_rate")), .Tsp = c(2004,
2019.91666666667, 12), class = c("mts", "ts", "matrix"))
Related
I have downloaded some raw data on inflation which said in the description that it has not been seasonally adjusted. Therefore I assumed that there is some seasonality present. I did not check if this is indeed true. What is the common way of checking a time-series for the presence of seasonality?
Nevertheless, I still tried to apply the procedure, but the before and after result are exactly the same; nothing has changed.
The code:
if (!require("tis")) {install.packages("tis"); library('tis')} # Load time series library
if (!require("seasonal")) {install.packages("seasonal"); library('seasonal')}
inflation.start <- c(1960,1)
inflation.end <- c(2018,1)
inflation.raw <- "rawData/germany_inflation.csv"
inflation.table <- read.table(inflation.raw, skip = 1, header = F, sep = ',', stringsAsFactors = F)
inflation.ger <- ts(inflation.table[,2], start = inflation.start, frequency = 4)
# ts.plot(inflation.ger)
inflation.seasadj <- final(seas(as.ts(naWindow(inflation.ger),freq=4))) # seasonal adjustment
inflation.seasadj.ger <- ts(inflation.seasadj, start = inflation.start, frequency = 4)
So apparently, inflation.ger and inflation.seasadj.ger are the exact same time-series. What could have gone wrong?
The data:
dput(inflation.ger)
structure(c(2.22222222222224, 1.244019138756, 0.75973409306742,
1.80608365019013, 1.98487712665404, 2.64650283553874, 2.73327049952876,
3.36134453781511, 3.15106580166824, 2.39410681399631, 2.47706422018348,
3.25203252032522, 2.87511230907457, 2.42805755395685, 3.31244404655327,
2.27471566054242, 2.09606986899562, 2.72168568920105, 2.2530329289428,
2.05303678357573, 3.07955517536358, 3.84615384615386, 3.98305084745763,
4.10729253981556, 4.06639004149377, 3.04526748971191, 2.93398533007336,
2.49597423510466, 1.8341307814992, 1.75718849840257, 1.10847189231985,
1.49253731343286, 1.25293657008615, 1.33437990580847, 1.80109631949884,
1.62538699690402, 2.01082753286931, 2.09140201394268, 1.92307692307691,
2.89413556740292, 3.33586050037907, 3.5660091047041, 4.00000000000001,
4.44115470022204, 5.06236243580337, 5.78754578754579, 5.66037735849054,
5.31537916371368, 4.88826815642457, 5.47091412742381, 6.25000000000001,
6.46029609690444, 7.39014647137152, 6.9599474720946, 7.30446024563674,
7.45891276864728, 7.06757594544325, 6.99815837937383, 6.44578313253009,
5.88235294117648, 6.25361899247252, 6.08146873207113, 5.43293718166383,
5.22222222222223, 4.30517711171662, 3.78583017847487, 3.70370370370372,
3.80147835269271, 3.81400208986417, 3.85617509119333, 3.46790890269152,
3.00101729399797, 2.86864620030195, 2.50878073256398, 2.50125062531265,
2.91358024691356, 3.27788649706457, 4.650024473813, 5.31966813079548,
5.51823416506719, 5.92136428233066, 5.19176800748362, 5.14365152919371,
5.72987721691677, 5.81395348837209, 6.66963094708762, 7.13970912296167,
5.89247311827958, 5.36770921386304, 5.08545227177989, 4.648292883587,
4.06173842404549, 3.28920978740473, 3.13367711225704, 2.71226415094341,
2.84933645589384, 2.83495145631071, 1.88461538461538, 2.06659012629162,
2.31499051233397, 2.30362537764349, 2.076255190638, 1.57480314960629,
0.741839762611279, 0, -0.332840236686399, -0.922849760059066,
-0.515463917525782, 0.0369139904023732, 0.519480519480511, 0.968703427719836,
0.962250185048109, 1.14391143911439, 1.29198966408267, 1.69741697416972,
2.4193548387097, 2.88215979569498, 2.80612244897959, 3.01161103047896,
2.72011453113812, 2.3049645390071, 2.72952853598016, 3.02923564635434,
2.84251480582282, 3.29915972330998, 4.51351791825871, 5.50437317784258,
5.9108527131783, 6.09404990403073, 4.95750708215298, 3.33642261353105,
4.66605672461115, 4.38715513342377, 4.5434098065677, 4.30493273542601,
2.97202797202796, 2.77296360485268, 2.58175559380379, 2.45055889939811,
2.07979626485568, 1.7284991568297, 1.5520134228188, 1.46873688627781,
1.45530145530146, 1.45047658516367, 1.36307311028499, 1.53019023986766,
1.76229508196721, 1.55228758169937, 2.32273838630808, 2.11812627291242,
1.24848973016513, 1.36765888978277, 0.597371565113501, 0.438771439968094,
0.198886237072386, 0.515873015873038, 0.673000791765629, 0.953137410643369,
1.54823342596267, 1.10540860639556, 1.37632717263074, 1.73092053501181,
1.72009382329947, 2.53807106598985, 2.01706749418153, 1.6627996906419,
1.99846272098384, 1.29474485910129, 1.21673003802282, 1.17915557246102,
1.13036925395631, 0.789473684210527, 1.05184072126221, 1.16541353383457,
0.968703427719814, 1.86497575531517, 1.82156133828996, 2.0066889632107,
1.62361623616237, 1.24496521420726, 1.64293537787514, 1.67577413479055,
1.70660856935367, 1.84448462929475, 1.4727011494253, 1.28986026513793,
1.7850767583006, 2.05965909090908, 2.26548672566371, 3.0774672798019,
2.94633461943178, 2.88796102992346, 3.08065074420214, 1.61290322580647,
0.81771720613288, 0.270544470747383, -0.235057085292139, 0.405268490374862,
0.811084825954715, 1.11298482293424, 1.11073712554695, 1.37907837201482,
1.87730472678512, 2.00133422281521, 2.19707057256989, 2.22295952222959,
2.13886146758801, 1.86396337475473, 2.01954397394136, 2.01233365790325,
1.54639175257732, 1.50882825040129, 1.62835249042147, 1.33630289532296,
1.20558375634519, 1.07526881720429, 0.848256361922726, 0.50235478806906,
0.0313479623824208, 0.469336670838559, 0.124610591900319, 0.312402374258052,
0.250705108116592, 0.0934288383680993, 0.466708151835709, 1.12114606041732,
1.87558612066271, 1.68014934660859, 1.73428305977082, 1.66307360640589,
1.50352868978214), .Tsp = c(1960, 2017.75, 4), class = "ts")
I'm trying to perform a rolling linear regression, whit overlapping windows and for different window sizes. I want to save the result in two tables, one with window size and slopes and one wiht window size a and intercepts.
My data set is now saved as a xts object. I'm trying to make a for-loop to generate the different window-sizes and then do a rolling regression between the two variables, with a overlapping window using rollapply. Then I would like that the coefficients for every regression get saved as a row in a matrix, that can be built on, so that every window size corresponds to one row. I have looked at a lot of previous questions, but I can not get it right.
I have hourly data for 2 variables, this is the data for the x-variable:
> dput(Xq$x)
structure(c(339.76625, 176.7196875, 142.8063125, 118.5785625,
102.0514375, 86.01156251, 86.99050001, 85.0089375, 380.0010626,
2114.279375, 2157.76875, 2442.575, 2562.6375, 2537.7125, 2581.888125,
1947.7575, 834.7918751, 765.1525001, 989.698125, 1433.2, 429.9081251,
388.333125, 1500.995, 1523.816625, 1529.090126, 439.746875, 1029.03625,
1470.07825, 1454.844813, 1448.8455, 413.7550001, 334.03125, 566.7362501,
1609.184375, 1509.266876, 1403.1425, 1142.695625, 795.138125,
1562.881875, 933.190625, 549.085625, 500.135, 535.83, 444.3493751,
356.386875, 268.1875001, 141.1878125, 119.658875, 162.0425625,
153.6944375, 161.0025, 151.37025, 155.9567501, 123.64825, 145.664125,
141.4480625, 232.2009375, 913.6480001, 2227.08125, 1870.618751,
2190.606251, 1357.81625, 824.555625, 699.99, 703.695, 620.74625,
581.2375001, 393.391875, 349.96625, 188.5445625, 154.03125, 142.0825,
339.7915625, 139.8941875, 154.6279376, 171.6016875, 151.1387501,
159.7665, 168.62025, 180.7596875, 447.2746875, 1550.11625, 1887.275,
1446.883125, 699.590625, 983.9925, 1319.62875, 769.505625, 812.713125,
638.1437501, 585.8312501, 626.7875, 1924.293125, 629.855625,
349.88375, 1038.54875, 1588.82225, 548.3475, 1053.368125, 964.825625,
990.324375, 1327.160625, 395.5862501, 421.8154376, 1308.551875,
1334.045, 1633.408125, 886.2662501, 1618.7975, 1325.59625, 847.0693751,
667.501875, 594.0531251, 249.920625, 210.8869376, 224.3725001,
209.6325, 213.64875, 210.3175001, 194.54, 90.1085625, 71.12575001,
70.69412501, 69.6075, 68.404625, 67.88837501, 67.317125, 67.220375,
67.696625, 273.2732501, 606.475625, 1277.3425, 913.24875, 612.5462501,
571.42125, 503.27375, 316.68375, 208.7436251, 127.283, 126.12375,
102.504625, 78.7938125, 70.0183125, 69.97900001, 77.7586875,
76.60543751, 94.5235625, 103.0095625, 105.1938125, 103.8090625,
104.005625, 104.544875, 105.2036875, 104.6611875, 375.7004375,
793.7725001, 782.544375, 257.065625, 387.1487501, 571.1912501,
356.6406251, 243.404375, 220.698125, 182.5680626, 161.060625,
166.5178125, 137.9805, 129.6253125, 99.4291875, 75.88075001,
65.769875, 62.62937501, 59.697875, 57.68675, 56.67275, 56.69425001,
57.296, 638.95125, 1210.92875, 990.09, 907.895625, 1122.704375,
569.139375, 295.6725, 263.21, 236.3885625, 153.935, 148.0899375,
161.72675, 102.1535, 115.8895, 114.2579375, 95.0023125, 90.72425,
84.2715, 71.06631251, 63.39812501, 75.2416875, 73.9420625, 72.26237501,
402.8870625, 1148.9775, 1058.86875, 896.47875, 890.9687501, 833.645625,
670.310625, 298.576875, 306.538125, 386.403125, 196.8343751,
174.0815, 156.6158126, 117.9345625, 105.095, 90.24362501, 87.08800001,
86.1628125, 105.3179375, 107.312625, 114.089, 104.85825, 95.9281875,
126.2874375, 529.7325626, 1533.605625, 1089.700625, 760.47, 1905.04125,
1744.460625, 1346.120625, 847.90625, 459.4625, 472.11, 474.5068751,
481.83875, 937.3618751, 267.1339376, 137.7895625, 124.0425625,
188.9461875, 108.8915, 111.67825, 84.319125, 127.1240625, 117.519125,
104.16225, 105.2490625, 158.5540625, 1215.278063, 1275.396875,
1301.14375, 1108.9225, 1280.390625, 1434.5225, 1038.926875, 599.3218751,
665.22875, 646.935, 487.604375, 236.8148126, 300.6626876, 830.2973126,
1286.612313, 403.0063751, 405.9081875, 156.5465625, 101.7661875,
100.2301875, 144.424625, 126.781125, 143.940625, 365.5354376,
849.313125, 1729.3175, 1762.6625, 1733.968751, 1275.4375, 1332.930625,
620.5625, 504.115625, 538.4556251, 433.5725, 337.094375, 225.183125,
184.7196251, 156.7545, 130.23325, 134.0796875, 145.196125, 153.243,
141.096375, 414.8042501, 304.7252501, 204.1889375, 129.7909375,
555.0276251, 1734.235625, 1780.209375, 1462.7825, 967.4743751,
1248.791875, 1001.655625, 662.92875, 546.801875, 393.72375, 308.85125,
259.985625, 280.439375, 274.1312501, 310.0375001, 270.3, 201.9288125,
219.6061875, 208.372625, 156.2023125, 162.5355626, 167.823875,
151.3928126, 151.42875, 293.7148125, 434.9101875, 943.9243751,
995.955, 614.055, 1387.864375, 1752.330626, 1238.1725, 1260.93,
565.383125, 253.179375, 275.66625, 280.4912501, 222.684375, 338.079875,
201.9365625, 136.7436875, 146.5479375, 142.794625, 150.3969375,
134.6478125, 88.22068751, 70.6445, 71.73737501, 243.176, 1559.0925,
1527.626876, 1260.648125, 1251.564375, 714.1075001, 1124.58,
901.6018751, 551.9075, 303.1025, 355.435625, 372.32375, 235.62125,
185.39475, 161.7701876, 155.4823751), index = structure(c(1438380000,
1438383600, 1438387200, 1438390800, 1438394400, 1438398000, 1438401600,
1438405200, 1438408800, 1438412400, 1438416000, 1438419600, 1438423200,
1438426800, 1438430400, 1438434000, 1438437600, 1438441200, 1438444800,
1438448400, 1438452000, 1438455600, 1438459200, 1438462800, 1438466400,
1438470000, 1438473600, 1438477200, 1438480800, 1438484400, 1438488000,
1438491600, 1438495200, 1438498800, 1438502400, 1438506000, 1438509600,
1438513200, 1438516800, 1438520400, 1438524000, 1438527600, 1438531200,
1438534800, 1438538400, 1438542000, 1438545600, 1438549200, 1438552800,
1438556400, 1438560000, 1438563600, 1438567200, 1438570800, 1438574400,
1438578000, 1438581600, 1438585200, 1438588800, 1438592400, 1438596000,
1438599600, 1438603200, 1438606800, 1438610400, 1438614000, 1438617600,
1438621200, 1438624800, 1438628400, 1438632000, 1438635600, 1438639200,
1438642800, 1438646400, 1438650000, 1438653600, 1438657200, 1438660800,
1438664400, 1438668000, 1438671600, 1438675200, 1438678800, 1438682400,
1438686000, 1438689600, 1438693200, 1438696800, 1438700400, 1438704000,
1438707600, 1438711200, 1438714800, 1438718400, 1438722000, 1438725600,
1438729200, 1438732800, 1438736400, 1438740000, 1438743600, 1438747200,
1438750800, 1438754400, 1438758000, 1438761600, 1438765200, 1438768800,
1438772400, 1438776000, 1438779600, 1438783200, 1438786800, 1438790400,
1438794000, 1438797600, 1438801200, 1438804800, 1438808400, 1438812000,
1438815600, 1438819200, 1438822800, 1438826400, 1438830000, 1438833600,
1438837200, 1438840800, 1438844400, 1438848000, 1438851600, 1438855200,
1438858800, 1438862400, 1438866000, 1438869600, 1438873200, 1438876800,
1438880400, 1438884000, 1438887600, 1438891200, 1438894800, 1438898400,
1438902000, 1438905600, 1438909200, 1438912800, 1438916400, 1438920000,
1438923600, 1438927200, 1438930800, 1438934400, 1438938000, 1438941600,
1438945200, 1438948800, 1438952400, 1438956000, 1438959600, 1438963200,
1438966800, 1438970400, 1438974000, 1438977600, 1438981200, 1438984800,
1438988400, 1438992000, 1438995600, 1438999200, 1439002800, 1439006400,
1439010000, 1439013600, 1439017200, 1439020800, 1439024400, 1439028000,
1439031600, 1439035200, 1439038800, 1439042400, 1439046000, 1439049600,
1439053200, 1439056800, 1439060400, 1439064000, 1439067600, 1439071200,
1439074800, 1439078400, 1439082000, 1439085600, 1439089200, 1439092800,
1439096400, 1439100000, 1439103600, 1439107200, 1439110800, 1439114400,
1439118000, 1439121600, 1439125200, 1439128800, 1439132400, 1439136000,
1439139600, 1439143200, 1439146800, 1439150400, 1439154000, 1439157600,
1439161200, 1439164800, 1439168400, 1439172000, 1439175600, 1439179200,
1439182800, 1439186400, 1439190000, 1439193600, 1439197200, 1439200800,
1439204400, 1439208000, 1439211600, 1439215200, 1439218800, 1439222400,
1439226000, 1439229600, 1439233200, 1439236800, 1439240400, 1439244000,
1439247600, 1439251200, 1439254800, 1439258400, 1439262000, 1439265600,
1439269200, 1439272800, 1439276400, 1439280000, 1439283600, 1439287200,
1439290800, 1439294400, 1439298000, 1439301600, 1439305200, 1439308800,
1439312400, 1439316000, 1439319600, 1439323200, 1439326800, 1439330400,
1439334000, 1439337600, 1439341200, 1439344800, 1439348400, 1439352000,
1439355600, 1439359200, 1439362800, 1439366400, 1439370000, 1439373600,
1439377200, 1439380800, 1439384400, 1439388000, 1439391600, 1439395200,
1439398800, 1439402400, 1439406000, 1439409600, 1439413200, 1439416800,
1439420400, 1439424000, 1439427600, 1439431200, 1439434800, 1439438400,
1439442000, 1439445600, 1439449200, 1439452800, 1439456400, 1439460000,
1439463600, 1439467200, 1439470800, 1439474400, 1439478000, 1439481600,
1439485200, 1439488800, 1439492400, 1439496000, 1439499600, 1439503200,
1439506800, 1439510400, 1439514000, 1439517600, 1439521200, 1439524800,
1439528400, 1439532000, 1439535600, 1439539200, 1439542800, 1439546400,
1439550000, 1439553600, 1439557200, 1439560800, 1439564400, 1439568000,
1439571600, 1439575200, 1439578800, 1439582400, 1439586000, 1439589600,
1439593200, 1439596800, 1439600400, 1439604000, 1439607600, 1439611200,
1439614800, 1439618400, 1439622000, 1439625600, 1439629200, 1439632800,
1439636400, 1439640000, 1439643600, 1439647200, 1439650800, 1439654400,
1439658000, 1439661600, 1439665200, 1439668800, 1439672400), tzone = "UTC", tclass = c("chron",
"dates", "times")), class = c("xts", "zoo"), .indexCLASS = c("chron",
"dates", "times"), tclass = c("chron", "dates", "times"), .indexTZ = "UTC", tzone = "UTC", .Dim = c(360L,
1L), .Dimnames = list(NULL, "x"))
And my y-variable:
> dput(Xq$y)
structure(c(-0.274050833, -0.236638333, -0.1994325, -0.174091667,
-0.153273333, -0.136978333, -0.124748333, -0.117348333, -0.147061667,
-0.346170833, -0.517939167, -0.575585833, -0.595914167, -0.563639167,
-0.53403, -0.5500525, -0.505650833, -0.471713333, -0.472485833,
-0.547393333, -0.390174167, -0.321545, -0.29781, -0.26912, -0.345084167,
-0.367618333, -0.279933333, -0.256805, -0.2514675, -0.314349167,
-0.3594375, -0.33482, -0.369094167, -0.4801075, -0.554780833,
-0.600498333, -0.604796667, -0.544491667, -0.636653333, -0.568401667,
-0.485494167, -0.453199167, -0.417475, -0.38417, -0.341585833,
-0.2821625, -0.248325, -0.2230575, -0.2449075, -0.2385375, -0.231885,
-0.214125, -0.194190833, -0.178575833, -0.1677675, -0.1615725,
-0.1739675, -0.2432125, -0.402414167, -0.448185833, -0.563599167,
-0.5855025, -0.55586, -0.516350833, -0.47892, -0.4603325, -0.434146667,
-0.37602, -0.320976667, -0.267863333, -0.250915, -0.241764167,
-0.271475, -0.2170225, -0.206605, -0.2088, -0.214511667, -0.2086825,
-0.203060833, -0.192895, -0.212629167, -0.319143333, -0.42647,
-0.4623275, -0.467844167, -0.506395833, -0.507088333, -0.496953333,
-0.511156667, -0.487846667, -0.4455525, -0.398383333, -0.565926667,
-0.429720833, -0.314555, -0.418586667, -0.578256667, -0.414858333,
-0.345411667, -0.3088925, -0.304373333, -0.334221667, -0.305029167,
-0.273269167, -0.315901667, -0.409731667, -0.500245833, -0.505959167,
-0.54742, -0.574725, -0.548458333, -0.5560675, -0.50246, -0.411618333,
-0.35965, -0.331884167, -0.312573333, -0.298478333, -0.289144167,
-0.274429167, -0.2218225, -0.198025833, -0.191955833, -0.1780825,
-0.157910833, -0.135935, -0.116965833, -0.099886667, -0.0864975,
-0.188904167, -0.325656667, -0.444044167, -0.5050425, -0.54236,
-0.547500833, -0.5399775, -0.521490833, -0.444911667, -0.388053333,
-0.327650833, -0.2478, -0.2026775, -0.1693425, -0.140848333,
-0.130440833, -0.103501667, -0.088843333, -0.09344, -0.126231667,
-0.158463333, -0.181145, -0.185095, -0.11657, -0.0349225, -0.223260833,
-0.431800833, -0.516, -0.487566667, -0.49941, -0.541773333, -0.511953333,
-0.4404425, -0.4021125, -0.380635, -0.3301275, -0.302468333,
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-0.158151667, -0.136234167, -0.117050833, -0.101201667, -0.08872,
-0.0855675, -0.257761667, -0.424794167, -0.528980833, -0.56834,
-0.591263333, -0.56574, -0.53178, -0.5410825, -0.552130833, -0.501294167,
-0.44576, -0.402855833, -0.316163333, -0.2515275, -0.213383333,
-0.186723333, -0.174315833, -0.170100833, -0.154446667, -0.147075833,
-0.169245, -0.188474167, -0.187344167, -0.2586975, -0.440815,
-0.534344167, -0.598391667, -0.613878333, -0.624658333, -0.583091667,
-0.508740833, -0.518310833, -0.51102, -0.4203825, -0.364895833,
-0.31302, -0.27689, -0.254130833, -0.232273333, -0.218198333,
-0.22501, -0.235655833, -0.242728333, -0.260448333, -0.263113333,
-0.243530833, -0.222301667, -0.274098333, -0.3974225, -0.484443333,
-0.506165, -0.6136375, -0.631805, -0.596274167, -0.539795, -0.446769167,
-0.398489167, -0.3986925, -0.4098625, -0.484515833, -0.375961667,
-0.291685, -0.273963333, -0.2621025, -0.2054525, -0.177625833,
-0.1564625, -0.141883333, -0.130685833, -0.121943333, -0.112834167,
-0.136975, -0.3204725, -0.458004167, -0.5262175, -0.527530833,
-0.520574167, -0.5800325, -0.561841667, -0.4909225, -0.4641625,
-0.443126667, -0.405705833, -0.3098625, -0.286379167, -0.30477,
-0.395341667, -0.38505, -0.356219167, -0.263050833, -0.219625833,
-0.197383333, -0.2019775, -0.226838333, -0.2333075, -0.2890475,
-0.3341175, -0.43458, -0.520441667, -0.577875, -0.568123333,
-0.551936667, -0.463691667, -0.468790833, -0.4747725, -0.4125925,
-0.394731667, -0.380213333, -0.308688333, -0.279549167, -0.249766667,
-0.233964167, -0.229904167, -0.244835833, -0.232436667, -0.215466667,
-0.198559167, -0.184533333, -0.185376667, -0.246823333, -0.395918333,
-0.4956775, -0.540474167, -0.5402375, -0.577863333, -0.561466667,
-0.503130833, -0.455221667, -0.4401875, -0.4187675, -0.389215,
-0.345275, -0.3378175, -0.348759167, -0.325149167, -0.29995,
-0.289409167, -0.291635, -0.301183333, -0.274799167, -0.2443375,
-0.2254225, -0.21272, -0.245265, -0.295081667, -0.356848333,
-0.4258325, -0.4329175, -0.487074167, -0.595525, -0.59333, -0.564645,
-0.464548333, -0.4294775, -0.425609167, -0.403769167, -0.353311667,
-0.282888333, -0.2464575, -0.231771667, -0.2275425, -0.224230833,
-0.218419167, -0.1902275, -0.161319167, -0.143495833, -0.133691667,
-0.181291667, -0.36056, -0.46681, -0.5194575, -0.532989167, -0.4899375,
-0.533224167, -0.4976575, -0.428966667, -0.412929167, -0.416463333,
-0.366666667, -0.316356667, -0.3023825, -0.282655, -0.267275833
), index = structure(c(1438380000, 1438383600, 1438387200, 1438390800,
1438394400, 1438398000, 1438401600, 1438405200, 1438408800, 1438412400,
1438416000, 1438419600, 1438423200, 1438426800, 1438430400, 1438434000,
1438437600, 1438441200, 1438444800, 1438448400, 1438452000, 1438455600,
1438459200, 1438462800, 1438466400, 1438470000, 1438473600, 1438477200,
1438480800, 1438484400, 1438488000, 1438491600, 1438495200, 1438498800,
1438502400, 1438506000, 1438509600, 1438513200, 1438516800, 1438520400,
1438524000, 1438527600, 1438531200, 1438534800, 1438538400, 1438542000,
1438545600, 1438549200, 1438552800, 1438556400, 1438560000, 1438563600,
1438567200, 1438570800, 1438574400, 1438578000, 1438581600, 1438585200,
1438588800, 1438592400, 1438596000, 1438599600, 1438603200, 1438606800,
1438610400, 1438614000, 1438617600, 1438621200, 1438624800, 1438628400,
1438632000, 1438635600, 1438639200, 1438642800, 1438646400, 1438650000,
1438653600, 1438657200, 1438660800, 1438664400, 1438668000, 1438671600,
1438675200, 1438678800, 1438682400, 1438686000, 1438689600, 1438693200,
1438696800, 1438700400, 1438704000, 1438707600, 1438711200, 1438714800,
1438718400, 1438722000, 1438725600, 1438729200, 1438732800, 1438736400,
1438740000, 1438743600, 1438747200, 1438750800, 1438754400, 1438758000,
1438761600, 1438765200, 1438768800, 1438772400, 1438776000, 1438779600,
1438783200, 1438786800, 1438790400, 1438794000, 1438797600, 1438801200,
1438804800, 1438808400, 1438812000, 1438815600, 1438819200, 1438822800,
1438826400, 1438830000, 1438833600, 1438837200, 1438840800, 1438844400,
1438848000, 1438851600, 1438855200, 1438858800, 1438862400, 1438866000,
1438869600, 1438873200, 1438876800, 1438880400, 1438884000, 1438887600,
1438891200, 1438894800, 1438898400, 1438902000, 1438905600, 1438909200,
1438912800, 1438916400, 1438920000, 1438923600, 1438927200, 1438930800,
1438934400, 1438938000, 1438941600, 1438945200, 1438948800, 1438952400,
1438956000, 1438959600, 1438963200, 1438966800, 1438970400, 1438974000,
1438977600, 1438981200, 1438984800, 1438988400, 1438992000, 1438995600,
1438999200, 1439002800, 1439006400, 1439010000, 1439013600, 1439017200,
1439020800, 1439024400, 1439028000, 1439031600, 1439035200, 1439038800,
1439042400, 1439046000, 1439049600, 1439053200, 1439056800, 1439060400,
1439064000, 1439067600, 1439071200, 1439074800, 1439078400, 1439082000,
1439085600, 1439089200, 1439092800, 1439096400, 1439100000, 1439103600,
1439107200, 1439110800, 1439114400, 1439118000, 1439121600, 1439125200,
1439128800, 1439132400, 1439136000, 1439139600, 1439143200, 1439146800,
1439150400, 1439154000, 1439157600, 1439161200, 1439164800, 1439168400,
1439172000, 1439175600, 1439179200, 1439182800, 1439186400, 1439190000,
1439193600, 1439197200, 1439200800, 1439204400, 1439208000, 1439211600,
1439215200, 1439218800, 1439222400, 1439226000, 1439229600, 1439233200,
1439236800, 1439240400, 1439244000, 1439247600, 1439251200, 1439254800,
1439258400, 1439262000, 1439265600, 1439269200, 1439272800, 1439276400,
1439280000, 1439283600, 1439287200, 1439290800, 1439294400, 1439298000,
1439301600, 1439305200, 1439308800, 1439312400, 1439316000, 1439319600,
1439323200, 1439326800, 1439330400, 1439334000, 1439337600, 1439341200,
1439344800, 1439348400, 1439352000, 1439355600, 1439359200, 1439362800,
1439366400, 1439370000, 1439373600, 1439377200, 1439380800, 1439384400,
1439388000, 1439391600, 1439395200, 1439398800, 1439402400, 1439406000,
1439409600, 1439413200, 1439416800, 1439420400, 1439424000, 1439427600,
1439431200, 1439434800, 1439438400, 1439442000, 1439445600, 1439449200,
1439452800, 1439456400, 1439460000, 1439463600, 1439467200, 1439470800,
1439474400, 1439478000, 1439481600, 1439485200, 1439488800, 1439492400,
1439496000, 1439499600, 1439503200, 1439506800, 1439510400, 1439514000,
1439517600, 1439521200, 1439524800, 1439528400, 1439532000, 1439535600,
1439539200, 1439542800, 1439546400, 1439550000, 1439553600, 1439557200,
1439560800, 1439564400, 1439568000, 1439571600, 1439575200, 1439578800,
1439582400, 1439586000, 1439589600, 1439593200, 1439596800, 1439600400,
1439604000, 1439607600, 1439611200, 1439614800, 1439618400, 1439622000,
1439625600, 1439629200, 1439632800, 1439636400, 1439640000, 1439643600,
1439647200, 1439650800, 1439654400, 1439658000, 1439661600, 1439665200,
1439668800, 1439672400), tzone = "UTC", tclass = c("chron", "dates",
"times")), class = c("xts", "zoo"), .indexCLASS = c("chron",
"dates", "times"), tclass = c("chron", "dates", "times"), .indexTZ = "UTC", tzone = "UTC", .Dim = c(360L,
1L), .Dimnames = list(NULL, "y"))
My code looks like this:
library(zoo)
mat_slope=matrix(nrow=i)
mat_intercept=matrix(nrow=i)
for(i in seq(from=24, to=240, by=24)){
mov.reg<- rollapplyr(Xq,
width= i,
by=24,
FUN = function(y,x)
{
coefficients(lm(formula=y~x, data = Xq))
},
by.column=FALSE)
mat_slope[i] <- coefficients(mov.reg)[2]
mat_intercept[i] <-coefficients(mov.reg)[1]
mat_intercept=rbind(i,mat_intercept)
mat_slope[n,i]=rbind(i, mat_slope)
}
I either get an empty matrix as result, or the following error message:
Error in merge.xts(res, xts(, idx, attr(data, "frequency"))) :
(list) object cannot be coerced to type 'double'
If anyone have some inputs or ideas it would be very appreciated! Thank's a lot!
mov.reg is not an lm objct, so it does not make sense to take coefficients of it. Also there is a reference to chron in the dput output so we need to load the chron package.
Xq is not specified but rather two separate xts objects are shown so we have assumed that those two are called x and y. Then create a single zoo object z from them. Now define a Coef function which takes a matrix with x and y columns and performs the indicated regression returning the coefficients. Also define roll which takes the width as input and runs rollapplyr with the desired arguments. Now use lapply to run roll with each width producing a list of zoo objects. This list has one component for each element in widths consisting of a zoo object with intercept and slope columns. Finally extract the intercepts from each component in the list and form a zoo object and do the same for the slopes. Note that if L is a list of zoo objects then do.call("merge", L) will produce a single zoo object from it.
library(xts) # this also loads zoo
library(chron)
# inputs are xts objects x and y
z <- cbind(x = as.zoo(x)[, 1], y = as.zoo(y)[, 1])
Coef <- function(m) coef(lm(y ~ x, as.data.frame(m)))
roll <- function(w) rollapplyr(z, w, Coef, by = 24, by.column = FALSE)
widths <- seq(24, 240, 24)
names(widths) <- widths # lapply will use these names for its output
L <- lapply(widths, roll)
intercepts <- do.call("merge", lapply(L, "[", TRUE, 1)) # extract 1st columns
slopes <- do.call("merge", lapply(L, "[", TRUE, 2)) # 2nd columns
Alternately do the rollapplyr twice replacing the last 3 lines with:
intercepts <- do.call("merge", lapply(widths, function(w) roll(w)[, 1]))
slopes <- do.call("merge", lapply(widths, function(w) roll(w)[, 2]))
This is my data:
data=structure(c(-0.0471957808923093, -0.0467988635384236, -0.0463342530558707,
-0.0457926330882236, -0.0451638382532273, -0.0444368569264807,
-0.0435998514313549, -0.0426401983500639, -0.0415445516030975,
-0.0402989307802484, -0.0388888369350307, -0.0372993976665075,
-0.0355155428026053, -0.0335222113649458, -0.0313045897396848,
-0.028848380109615, -0.026140097233332, -0.023167390606974, -0.0199193879382963,
-0.0163870547327459, -0.0125635636730607, -0.00844466640840535,
-0.00402905939999997, 0.000681265356828354, 0.00568069455370951,
0.0109597029612447, 0.01650460835736, 0.0222973821907433, 0.0283155256820092,
0.0345320202245192, 0.0409153597579977, 0.0474296712607441, 0.0540349276635842,
0.0606872553679083, 0.0673393362019039, 0.0739409011365642, 0.0804393104801724,
0.0867802126590783, 0.0929082711616744, 0.0987679468617816, 0.104304320836165,
0.109463941032544, 0.114195674804447, 0.11845154847061, 0.122187554726899,
0.125364408967776, 0.127948236372159, 0.12991117296429, 0.131231865742443,
0.131895859325063, 0.131895859325063, 0.131231865742443, 0.12991117296429,
0.127948236372159, 0.125364408967776, 0.122187554726899, 0.11845154847061,
0.114195674804447, 0.109463941032544, 0.104304320836165, 0.0987679468617816,
0.0929082711616744, 0.0867802126590783, 0.0804393104801724, 0.0739409011365642,
0.0673393362019039, 0.0606872553679083, 0.0540349276635841, 0.0474296712607441,
0.0409153597579976, 0.0345320202245192, 0.0283155256820092, 0.0222973821907433,
0.01650460835736, 0.0109597029612447, 0.00568069455370951, 0.000681265356828344,
-0.00402905939999997, -0.00844466640840537, -0.0125635636730607,
-0.0163870547327459, -0.0199193879382963, -0.023167390606974,
-0.026140097233332, -0.028848380109615, -0.0313045897396848,
-0.0335222113649458, -0.0355155428026053, -0.0372993976665075,
-0.0388888369350306, -0.0402989307802484, -0.0415445516030976,
-0.0426401983500639, -0.0435998514313549, -0.0444368569264807,
-0.0451638382532273, -0.0457926330882236, -0.0463342530558707,
-0.0467988635384236, -0.0471957808923093, -169.075778315231,
-165.419424999945, -161.763071684659, -158.106718369373, -154.450365054087,
-150.794011738801, -147.137658423515, -143.481305108229, -139.824951792942,
-136.168598477656, -132.51224516237, -128.855891847084, -125.199538531798,
-121.543185216512, -117.886831901226, -114.23047858594, -110.574125270654,
-106.917771955368, -103.261418640081, -99.6050653247953, -95.9487120095092,
-92.2923586942231, -88.636005378937, -84.9796520636509, -81.3232987483648,
-77.6669454330787, -74.0105921177926, -70.3542388025065, -66.6978854872204,
-63.0415321719343, -59.3851788566482, -55.7288255413621, -52.072472226076,
-48.4161189107899, -44.7597655955038, -41.1034122802177, -37.4470589649316,
-33.7907056496455, -30.1343523343594, -26.4779990190733, -22.8216457037872,
-19.1652923885011, -15.508939073215, -11.8525857579289, -8.19623244264278,
-4.53987912735666, -0.88352581207058, 2.77282750321554, 6.42918081850162,
10.0855341337877, 13.7418874490738, 17.3982407643599, 21.054594079646,
24.7109473949321, 28.3673007102183, 32.0236540255043, 35.6800073407905,
39.3363606560765, 42.9927139713627, 46.6490672866487, 50.3054206019349,
53.9617739172209, 57.6181272325071, 61.2744805477931, 64.9308338630793,
68.5871871783654, 72.2435404936515, 75.8998938089376, 79.5562471242237,
83.2126004395098, 86.8689537547959, 90.525307070082, 94.1816603853681,
97.8380137006542, 101.49436701594, 105.150720331226, 108.807073646513,
112.463426961799, 116.119780277085, 119.776133592371, 123.432486907657,
127.088840222943, 130.745193538229, 134.401546853515, 138.057900168801,
141.714253484087, 145.370606799374, 149.02696011466, 152.683313429946,
156.339666745232, 159.996020060518, 163.652373375804, 167.30872669109,
170.965080006376, 174.621433321662, 178.277786636948, 181.934139952235,
185.590493267521, 189.246846582807, 192.903199898093), .Dim = c(100L,
2L), .Dimnames = list(NULL, c("Y", "X")))
With this data I can plot this graph below:
plot(data[,1],data[,2],type="l")
abline(h=quantile(data[,2],0.75))
abline(h=quantile(data[,2],0.25))
Using polygon function how can I shade the area (with different colors) between the distribution tails and 0.75/0.25 quantiles lines?
An answer:
Let dat be your data frame,
oo <- dat[24:76, ];
oo[1, ] <- c(dat[1,1], dat[25,2]);
oo[, nrow(oo)] <- c(dat[100,1], dat[75,2]);
plot(dat, type = "l"); polygon(oo, col = "gray")
i am facing a problem in plot ols estimations in a scatterplot:
I have this data frame: With 9 columns and 99 rows:
structure(list(Y = c(-0.145442175, 0.291096141, 0.489923112,
-2.038363166, 1.180430664, 0.188114666, 0.850922634, 1.172142766,
-3.980837975, 0.285762444, 2.497040646, 0.658010994, -0.925171981,
0.37076995, -1.108211119, -0.409242669, -1.234583525, -0.385841816,
0.016744771, -0.584406288, 1.17224811, -0.746804388, -0.625028046,
0.257871468, -2.735845346, 2.619304857, -0.406825232, 0.323665151,
2.218951363, -0.821029648, -0.872854889, -2.663306158, -0.121976044,
0.881566376, -1.972706678, -3.855576256, 2.927421113, 1.314753531,
0.234296206, 0.828464757, -0.909318569, 0.616134903, -0.567630403,
0.624571064, -0.414112923, 0.642200314, -0.309421266, 0.195312598,
-0.519988256, 0, 0.081070175, 0.032446432, -0.534025032, -0.426783307,
-0.38495511, -0.207900219, -1.953789746, -0.616924355, -0.783222881,
-1.935420969, 0.638445535, 1.080925923, -1.598076681, 0.25063631,
-0.697183766, 0.188971653, -0.415267389, -4.154506044, 1.163226552,
0.036569698, -0.547147074, 1.11937374, 0.383311682, -0.875037781,
-0.372684863, 0.306816004, -1.250561544, -1.042237738, -1.757788446,
0.021079982, 1.844023775, 1.674645753, -0.428546132, -0.527705597,
0.542202572, -0.621479123, -0.050415867, -0.122332943, 0.468553764,
0.216998274, 3.088480781, 0.434099931, 2.114916704, -2.407018936,
-0.127060127, 0.546756422, 0.263207486, 0.63453915, 0.76832746
), X = c(0.009476137, -0.0236354, 0.0094081, 0.11715252, 0.032324021,
0.0461193, 0.050794971, 0.032372819, 0.202121874, 0.390821859,
-0.124492596, -0.127305193, -0.22233597, -0.081113713, 0.09952616,
0.22494711, 0.226621495, 0.411607624, 0.089200478, -0.013454832,
-0.013547165, -0.232366214, 0.03140992, -0.026798837, -0.084556341,
-0.091993172, -0.303730207, -0.236679148, -0.284235285, -0.355253166,
-0.179645537, -0.01381843, -0.022950244, -0.050065976, -0.032018504,
-0.087168055, -0.081865767, -0.253991077, -0.242882759, -0.150225053,
-0.16596575, -0.156887247, -0.071795146, -0.100408802, -0.067307731,
0.024006869, -0.019250912, -0.02399429, 0.038421097, 0.062320065,
0.07187025, 0.024019462, 0.038421097, 0.033539309, 0.014351457,
-0.009575137, 0.014343968, 0.028561284, 0.0404213, 0.026065697,
-0.004700435, -0.072739794, -0.042217496, -0.05889531, -0.130522139,
-0.136291869, -0.120099035, -0.091418565, -0.122040844, -0.124609029,
-0.096255449, -0.190338762, -0.11611752, -0.055598423, -0.065293448,
-0.038746326, -0.029090518, -0.067627348, -0.082097445, -0.215845836,
-0.389993696, -0.264371785, -0.126530291, -0.111840985, -0.094952196,
-0.136700196, -0.190968195, -0.156564122, -0.181077278, -0.15381292,
-0.122020692, -0.107867301, -0.068642333, -0.034348677, -0.073289926,
-0.063314884, -0.092537576, -0.165375956, -0.15042398), Null = c(-0.036795117836493,
0.0120555676565338, -0.0366906491623935, -0.22323992930528, -0.0728300398338213,
-0.0955073599141197, -0.103350601084975, -0.0729090354522075,
-0.400153521158964, -0.887015257107641, 0.1362666683468, 0.13919994231771,
0.221388292373518, 0.087380368104602, -0.189831042487278, -0.452154909992189,
-0.456044210600938, -0.948567833126862, -0.170785020294756, -0.00253939338337472,
-0.00240533038312774, 0.228145471304061, -0.0713518661553421,
0.0165138860659871, 0.0915102566139487, 0.100284493544177, 0.265652059802101,
0.230938443729295, 0.257246215885006, 0.281209408151878, 0.188533028671265,
-0.00201164134414489, 0.0110851592192505, 0.0481858583559124,
0.0237904823161768, 0.094614581053392, 0.0882862377341187, 0.241468070168396,
0.234837060900023, 0.162029971029324, 0.176601607696189, 0.168307425791361,
0.0759851164110966, 0.109970788582389, 0.0703849242291975, -0.059492586621119,
0.00581616568295407, 0.0125631925046972, -0.0827672867080164,
-0.123023227393077, -0.139691063870559, -0.0595125909296922,
-0.0827672867080164, -0.074799966578053, -0.044324863847201,
-0.00820062690976645, -0.0443132308515717, -0.0667648997869916,
-0.0860567642206439, -0.0627706942069095, -0.0153914247452083,
0.0771546773236518, 0.0377224646820258, 0.0596889425617937, 0.1425196179012,
0.148379247725525, 0.13162698340227, 0.0996137276510431, 0.133686233062275,
0.136388667637584, 0.105222539655097, 0.197385328960716, 0.127361748973716,
0.0554268640818151, 0.0678473149754353, 0.0330232883757411, 0.0197208677278167,
0.0707862239701058, 0.0885648870712001, 0.216820906265572, 0.286245951224793,
0.247258814186372, 0.138394666330137, 0.122716205945161, 0.103719679674083,
0.148789344619283, 0.197893429730301, 0.168006688568371, 0.189742414352596,
0.165430712615822, 0.133664933948451, 0.11833998959919, 0.0720581343490991,
0.0270069004188009, 0.077834296346802, 0.0653403280475977, 0.100918894574441,
0.176071877748707, 0.162219750035618), OLS_1 = c(-2.97674658085357,
-2.95792547866683, -2.97674412477729, -2.7937460366665, -2.96913739819288,
-2.95639989365184, -2.95069150171007, -2.96910314906723, -2.3856485268894,
-0.647452287114872, -2.68293610049662, -2.670570393744, -2.10297963546522,
-2.84137496711892, -2.84927190111917, -2.23638642750757, -2.22477621905134,
-0.385841816000001, -2.87715002139054, -2.96747293407547, -2.96740133507642,
-2.02609643038743, -2.9697648045679, -2.95427875550959, -2.8310157181346,
-2.80733412921436, -1.38551048535346, -1.99204069101103, -1.57679230211392,
-0.821029648, -2.39395151432173, -2.96718943992586, -2.95867282134313,
-2.9175506236826, -2.94755679517459, -2.82290206987746, -2.83914454134393,
-1.84931168689084, -1.94200482386918, -2.56030139156351, -2.4747687889082,
-2.52507434784403, -2.86749990988846, -2.77838660436577, -2.87908253396987,
-2.97385415360498, -2.96244666805069, -2.95752797222193, -2.96426392038595,
-2.93361303993881, -2.91621877029975, -2.97384869333029, -2.96426392038595,
-2.96826157356433, -2.97653443074828, -2.97023260580068, -2.97653534550966,
-2.9715473503959, -2.96240424133875, -2.97289412424858, -2.9730125951007,
-2.86497897723402, -2.93188917574701, -2.89904800305061, -2.6561144854951,
-2.62935195635151, -2.70174255054932, -2.80922741244202, -2.69350740105694,
-2.68242924921473, -2.79295820376613, -2.32657978700299, -2.718248099245,
-2.90625073580661, -2.88407071600265, -2.93759776247538, -2.95143559806685,
-2.87827902655775, -2.83845377816351, -2.15100018436527, -0.392139380784325,
-1.7590965971582, -2.67400272569948, -2.73540774982849, -2.79741598960129,
-2.62741730304073, -2.322499279269, -2.52681590220219, -2.38514457172383,
-2.541507865502, -2.6935934995898, -2.75082409521646, -2.87570553083222,
-2.94427256930162, -2.86349763526591, -2.88884317216564, -2.80553055841713,
-2.47811758528604, -2.55927025907886), OLS_2 = c(-2.83865555876367,
-2.82203271957637, -2.83865550287755, -2.66277932892391, -2.83073328950317,
-2.8182826854432, -2.81275284604234, -2.83069942358793, -2.27571536741022,
-0.632851535784811, -2.56646067709365, -2.55491098827374, -2.02364579120999,
-2.71420058960775, -2.71564453925406, -2.13442002502496, -2.12343285482248,
-0.385841816, -2.74223576659719, -2.83068449367348, -2.83062014186059,
-1.95158880862936, -2.83135434505306, -2.81870405841395, -2.70456098525177,
-2.68251016192609, -1.35080974869909, -1.91966655284606, -1.53026524143009,
-0.821029648, -2.29619548286091, -2.83042962848176, -2.82271365766308,
-2.78489427206998, -2.81254809712918, -2.69700817487578, -2.71212546804251,
-1.78585373408616, -1.87276085874404, -2.45184700668681, -2.37183555552258,
-2.41889982491589, -2.73848954857785, -2.65553364194069, -2.74924637290594,
-2.8354502300085, -2.82614423798244, -2.82167034953476, -2.82594242161564,
-2.7962902949221, -2.77959589724382, -2.83544467118397, -2.82594242161564,
-2.82986834510621, -2.83829410413293, -2.83315419155684, -2.83829521382395,
-2.83312719078141, -2.82412509152621, -2.83447802392599, -2.83561001727694,
-2.73614728712302, -2.79813447119318, -2.76776591170989, -2.54140667394362,
-2.5163996858597, -2.58402223424852, -2.68427373122372, -2.57633280462435,
-2.56598731123967, -2.66911582708562, -2.23311605677819, -2.59943103595799,
-2.7744383205277, -2.75387620457868, -2.80339428073398, -2.81610308322424,
-2.74850042856033, -2.71148276169435, -2.06864445166113, -0.418358709691658,
-1.7012556906544, -2.558117011201, -2.61544592452239, -2.67326984561107,
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-2.80953310903525, -2.73477077084888, -2.75830410348864, -2.68083005992821,
-2.37496906485549, -2.4508827380889), OLS_3 = c(-2.58083646581942,
-2.5683178338716, -2.58084089114316, -2.41826149362172, -2.57232965672457,
-2.56041470241702, -2.55521822468909, -2.57229650627193, -2.0704676472292,
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-2.47676312148376, -2.46615920192222, -1.94404642215785, -1.9342224786085,
-0.385841816000001, -2.49034777076914, -2.57529735049815, -2.57524652934739,
-1.81248137667339, -2.57293885513887, -2.56558300171966, -2.46846711008925,
-2.44946096338359, -1.28602268062379, -1.78454238349805, -1.4433981562183,
-0.821029648, -2.11368273887782, -2.57509593622485, -2.56887479307252,
-2.53722183306237, -2.56048377359198, -2.46196139684977, -2.47497795642607,
-1.66737628649693, -1.7434807939705, -2.24936019247138, -2.17965685727221,
-2.22066956504207, -2.49762425675709, -2.42616435450559, -2.50683929408026,
-2.57704694280319, -2.57166448720316, -2.56802106429762, -2.56769302344379,
-2.53990559282486, -2.52451787208599, -2.57704119998386, -2.56769302344379,
-2.57148502596854, -2.58019625622877, -2.57722566059429, -2.58019772985789,
-2.57469359055957, -2.56595475982599, -2.57605200249485, -2.57907626550515,
-2.49561557851369, -2.54841138215235, -2.52265924802504, -2.32724456926626,
-2.30551521644622, -2.36423571438323, -2.45098235381054, -2.35756515622,
-2.3485875529132, -2.43789928063234, -2.05861713726078, -2.37759686441414,
-2.52834152993493, -2.51080007744427, -2.55283331443161, -2.56343418632904,
-2.50620082129485, -2.47442497328161, -1.91488441727801, -0.467310795744689,
-1.59326539683083, -2.34175573481226, -2.39147445613669, -2.44148615865099,
-2.30394357612981, -2.05528024243402, -2.22208856552246, -2.10648769733616,
-2.23405702128991, -2.35763491117015, -2.40392966200837, -2.50415507637054,
-2.55797145858227, -2.49443477420494, -2.51458468009137, -2.44801138045477,
-2.18238842077399, -2.24852076027753), OLS_4 = c(-2.4289478285331,
-2.41681903415288, -2.42895104301202, -2.27867081965274, -2.4213161496905,
-2.41038194422522, -2.40559515788832, -2.42128586809391, -1.95522949388955,
-0.590647453749078, -2.21077815389366, -2.20138321248198, -1.76758669368012,
-2.33060054299992, -2.32313500877883, -1.83755181381677, -1.82840597739465,
-0.385841816, -2.34557046847711, -2.42346978407977, -2.42342111188123,
-1.70861264386732, -2.42187239429871, -2.41422413566286, -2.32281181955877,
-2.30497392699143, -1.21632553238408, -1.68248005204524, -1.36346128591018,
-0.781669317752002, -1.99042352676657, -2.42327691796255, -2.41734804581689,
-2.38744248609079, -2.40939495374384, -2.31670510436427, -2.32892438647688,
-1.57289978140148, -1.64407512538075, -2.11744278294415, -2.05217911016675,
-2.09057710272701, -2.35019495754122, -2.28311871426765, -2.35885543710246,
-2.42560672084754, -2.42000135641999, -2.4165372393818, -2.41707097497419,
-2.39145946177805, -2.3772271125231, -2.42560153071694, -2.41707097497419,
-2.420544236609, -2.42841594588832, -2.4253216199613, -2.42841722040367,
-2.42347169955882, -2.41547562547196, -2.42470587973943, -2.4271143253132,
-2.34830761179908, -2.39799094116799, -2.37373288731684, -2.19039487337143,
-2.17003793409615, -2.22505776553193, -2.30640152341961, -2.21880622042115,
-2.21039315621698, -2.294126428977, -1.93888869626962, -2.23758086989921,
-2.37908034073483, -2.36257901260101, -2.4021644964107, -2.41218787827608,
-2.35825527028976, -2.3284051877118, -1.80440438182757, -0.451087514089169,
-1.50359480720157, -2.20399138892979, -2.25058992243427, -2.29749148286179,
-2.16856567860513, -1.93576601076367, -2.09190575790345, -1.98368936201681,
-2.10311255036163, -2.21887159162467, -2.26226743315126, -2.35633238493592,
-2.407018936, -2.34719820268328, -2.36613768370737, -2.30361375259329,
-2.05473632620086, -2.11665669129059), OLS_5 = c(-2.2911912568638,
-2.28123967681215, -2.29119683586224, -2.14805590207021, -2.28325670505768,
-2.27261386268403, -2.268006850245, -2.28322682471889, -1.84560662105751,
-0.576090713535621, -2.0945064647732, -2.0859234999636, -1.68828464788266,
-2.20368547406672, -2.18986194988925, -1.73587625378362, -1.72735189094969,
-0.385841816, -2.21101101562234, -2.28700200417098, -2.28696051646281,
-1.63411554699496, -2.28380625780731, -2.27896044246845, -2.19661244829441,
-2.18039652225164, -1.18146437845759, -1.6101070827248, -1.31682391434599,
-0.781364138557704, -1.89278224977018, -2.28683751979873, -2.28170279433502,
-2.25507742887343, -2.27469315563211, -2.19106352335337, -2.20216376634672,
-1.50940418054145, -1.57481865165838, -2.00915316980509, -1.94938461398854,
-1.98455653642811, -2.22145418758665, -2.1605019074557, -2.22929361026136,
-2.28754415075922, -2.28401553991566, -2.28099274980288, -2.2790962708342,
-2.25448944582185, -2.24095826297856, -2.28753886744317, -2.2790962708342,
-2.28249611688223, -2.29051254450738, -2.28856644852124, -2.29051401027405,
-2.28539476406181, -2.27754391464367, -2.28663199585719, -2.29003809100396,
-2.21974449731936, -2.26453458741267, -2.24273365564754, -2.0758820670505,
-2.05727208640147, -2.1075473897372, -2.18169509790509, -2.10183883759691,
-2.0941547862828, -2.17052540371127, -1.84552009498619, -2.11897925887711,
-2.2475539961602, -2.23266092019845, -2.26826235385205, -2.27716458812284,
-2.22875067319638, -2.20169236013157, -1.72209385129724, -0.476893951190187,
-1.44569200778405, -2.08830648613957, -2.13084935049209, -2.17358829667077,
-2.05592583172644, -1.84265559786228, -1.98577321824112, -1.88660772323127,
-1.99603456442263, -2.10189853669134, -2.14149931364702, -2.22701080101746,
-2.27258448425562, -2.21873931960315, -2.23587705524471, -2.17915915787995,
-1.95172754860073, -2.00843362344438), OLS_6 = c(-2.14615029819501,
-2.1274826763545, -2.14613692884822, -2.038363166, -2.14482079785526,
-2.13839956793073, -2.1352633011825, -2.14480554064275, -1.77137087834078,
-0.604458131512312, -1.92044345866761, -1.91142894340333, -1.5035051350835,
-2.03720410348948, -2.07364942604987, -1.67230210256299, -1.66457879312031,
-0.427523081653794, -2.09111249534671, -2.1358169999572, -2.13575175544593,
-1.44873737433719, -2.14509683128765, -2.12442374236989, -2.02946586195686,
-2.01185030632841, -0.994510606111227, -1.42450007218492, -1.12983335353955,
-0.596198212559954, -1.7115906309286, -2.13555900800151, -2.12811588444992,
-2.09509015766854, -2.11889016916752, -2.02341958358771, -2.03553614239934,
-1.32305159796573, -1.38891263096519, -1.83141440901763, -1.76969899713653,
-1.80596583024281, -2.05682837956465, -1.99043348930533, -2.06558998487816,
-2.14664801486533, -2.13135448546891, -2.1271468279034, -2.14250449627423,
-2.12545741758249, -2.11509475538252, -2.1466464083569, -2.14250449627423,
-2.14442504670383, -2.14684049810003, -2.13838680613343, -2.1468398441846,
-2.14583791450693, -2.14156460788614, -2.14633891192499, -2.14114136796206,
-2.05492693125432, -2.10632999229998, -2.08080895764288, -1.90090288083161,
-1.88144765246016, -1.93417313784094, -2.01325520240903, -1.9281579797124,
-1.92007377040746, -2.00120005643771, -1.66327168223962, -1.94624457366434,
-2.08634430885867, -2.06937728900294, -2.11086434271986, -2.12206882778948,
-2.06498074945642, -2.03501978622706, -1.5377512452434, -0.29431817292714,
-1.25902518147068, -1.91393009686737, -1.95881793980313, -2.00449939786682,
-1.88004274517372, -1.66034827254381, -1.80722288608151, -1.70526848086161,
-1.81783189921089, -1.92822084254891, -1.97013652098612, -2.0630309651189,
-2.1162243283256, -2.0538104595074, -2.07300962091288, -2.0105124912345,
-1.7721107506457, -1.83066883021211)), .Names = c("Y", "X", "Null",
"OLS_1", "OLS_2", "OLS_3", "OLS_4", "OLS_5", "OLS_6"), row.names = c(NA,
99L), class = "data.frame")
My scatter plot will consist of the first column (Y) and the second column (X).
The third column i will not use.
From the fourth column are the curves that are fitted values of OLS regressions.
How do I include them using the plot function?
i am doing this, but its not working
plot(data[,2],data[,1])
for(i in 4:9){
lines(data[,i])
}
What am i doing wrong?
Basically you want
data <- data[order(data$X), ] ## reordering so that `X` is increasing
plot(data$X, data$Y)
for (i in 4:9) {
lines(data$X, data[,i], col = i) ## remember to set `x-coordinates`
}
legend("topright", legend = names(data)[4:9], col = 4:9, lty = 1) ## add legend
We used the R library forecast to make predictions for the next 24 hours. We have the following:
fore_cast=forecast.tbats(model,h=24,level=90)
fore_cast
Point Forecast Lo 90 Hi 90
5.380952 6270.778 5389.089 7296.643
5.386905 5458.096 4557.375 6536.743
5.392857 5219.995 4248.967 6412.814
5.398810 5187.102 4126.390 6520.328
Now we have 2 problems:
We need 'time' (in hour e.g. 01,23,19 etc) instead of 'point'.
We wish to plot the trendline against time showing the actual observed
values against these predicted values. We have loaded actual observed
values from a CSV file.
We tried:
actual_data = read.csv('actualdata.csv')
plot(actual_data,fore_cast)
Doesn't work, and using plot(actual_data) just shows some points in a straight line instead of curved trendline.
EDIT:
Sample output of fore_cast from dput:
structure(list(model = structure(list(lambda = 0.000438881055939422,
alpha = 0.65694875480321, beta = -0.0983972877836753, damping.parameter = 0.800419363290521,
gamma.one.values = c(-0.00150031474145603, -0.00124696854910294
), gamma.two.values = c(0.0023600487982342, -0.002465549595849
), ar.coefficients = NULL, ma.coefficients = NULL, likelihood = 13202.294346586,
optim.return.code = 0L, variance = 0.00855092137349485, AIC = 13258.294346586,
parameters = structure(list(vect = c(0.000438881055939422,
0.65694875480321, 0.800419363290521, -0.0983972877836753,
-0.00150031474145603, -0.00124696854910294, 0.0023600487982342,
-0.002465549595849), control = structure(list(use.beta = TRUE,
use.box.cox = TRUE, use.damping = TRUE, length.gamma = 4L,
p = 0, q = 0), .Names = c("use.beta", "use.box.cox",
"use.damping", "length.gamma", "p", "q"))), .Names = c("vect",
"control")), seed.states = structure(c(7.44188559667267,
0.00357069100887873, -0.0664300680553579, 0.0229067500159256,
0.00460111570469819, -0.00772324725408007, -0.000610110386029883,
0.00568378752162509, -0.0084050648066819, -0.0324093004247092,
-0.000720936399990958, -0.00705790547321605, -0.00738992950838566,
0.00180424326179638, -0.00107745502434416, 0.00242014705705761,
-0.01824679745657, 0.0123019701003545, -0.0245935735677402,
0.0181321397860132), .Dim = c(20L, 1L)), fitted.values = structure(c(1598.57443298879,
1435.74973092922, 1397.92464316794, 1296.90202189518, 1440.3201303663,
1544.11695101118, 1777.97079874181, 1766.50571671645, 1925.27360388028,
1863.26963233038, 1773.08363764691, 1887.26580055295, 1887.48006609474,
1841.66200850472, 1991.90290660363, 2233.04775631848, 2081.30246965768,
1872.12639817609, 1899.38583561568, 2213.43437455052, 2214.00832820531,
1745.36311914995, 1678.67975050944, 1502.35472259274, 1512.27350460399,
1456.14165844166, 1464.3803467642, 1517.99443293857, 1484.54280422369,
1382.37041287489, 1452.43700910726, 1545.16934543365, 1440.50974319508,
1475.59742668699, 1544.88546424501, 1790.95280713647, 1916.4267023671,
1928.72804180587, 1819.15839770808, 1916.43079357329, 1836.80043977753,
1720.25638746452, 1730.03629161412, 1614.6048115754, 1599.23641723244,
1635.86950932066, 1543.46360784778, 1641.35066985679, 1608.60556151299,
1651.47649465456, 1475.15006990464, 1403.67294742438, 1507.58932406857,
1666.3170708439, 1696.06132797576, 1543.32187293056, 1704.58043626911,
1914.72424191575, 2109.33624862625, 2092.98934458578, 2222.13355258602,
2084.68677709368, 1962.9230489947, 2045.61547393981, 2140.30565941261,
2097.46130996426, 2126.07936955385, 2226.18935508502, 2269.54492801286,
2300.37314952852, 2398.48786829541, 2303.31270702723, 2332.74139979969,
2146.51487558643, 2101.27480789243, 2111.61910899422, 2053.57840714969,
2046.56606362537, 2073.82870990658, 2094.88831798868, 2334.85185938782,
2541.72156227893, 2502.36031483721, 2398.12240784327, 2266.35832277135,
2151.05248890962, 2266.88803633019, 2366.19453856405, 2399.97570044332,
2341.74959623409, 2144.33465155869, 2102.91952061083, 2214.48622101851,
2179.48115699957, 2288.28092735955, 2224.55218736155, 2195.1506809087,
2163.94619334319, 2161.41843642149, 2134.75060670667, 2138.77895768654,
2142.84680080931, 2258.55072549978, 2297.90237035988, 2314.94197015208,
2300.99928929609, 2277.39754662665, 2291.06980363364, 2487.04257346235,
2381.05768214413, 2509.40078456481, 2657.61336243367, 2528.65026804303,
2434.2722174014, 2366.04811963942, 2270.6647135766, 2231.33965004538,
2376.51043520344, 2249.42861599343, 2193.98771109322, 2252.12327312365,
2210.76969838623, 2180.50451255189, 2221.92898123682, 2537.84678083006,
2329.57350097532, 2252.82349908982, 2143.92033677754, 2092.3142840022,
2084.70304624685, 2111.18929138546, 2160.05383108999, 2280.94409931504,
2118.22029344747, 2214.65738250204, 2269.05911898631, 2084.26658709038,
2016.04764576402, 2095.57091797435, 2161.07354463394, 2427.77607700887,
2333.91103594967, 2234.23838054763, 2250.71557301013, 2186.97925802073,
2129.51096829218, 2115.40228652934, 2094.89231085691, 2086.41044567131,
2180.94542608489, 2105.38187642016, 2459.45788915933, 2292.36325639374,
2410.75372754831, 2375.56640249604, 2491.11938114866, 2470.51372278037,
2464.95765202085, 2600.85929020727, 2709.48518695182, 2779.77558137814,
2518.29927341458, 2344.06621605191, 2391.56719713269, 2368.68842788795,
2199.93530349068, 2113.92970206565, 2458.96718445444, 3121.97852988865,
2559.40932439262, 2331.12829078836, 2238.54586985577, 2241.91440620202,
2225.29804576634, 2154.14147781021, 2060.57980596908, 2037.30100544426,
2215.93410789353, 2364.42668160056, 2518.72871618042, 2537.34279365294,
2473.76096855791, 2623.63387707374, 2589.08335304697, 2577.0563838788,
2349.53279218826, 2305.52193868551, 2232.63712180453, 2167.50003597208,
2320.23187534213, 2281.86365949586, 2281.21119271599, 2323.2014703372,
2185.94404743238, 2140.21863271207, 2011.67723856012, 1966.52063119589,
2002.67344212857, 1952.41101080662, 1988.37461163105, 2126.75137749373,
2239.14722292367, 2320.98046489603, 2444.91847853015, 2431.69548763034,
2514.73820659393, 2505.85249387343, 2888.19773974179, 2853.20690693738,
2502.20865871069, 2524.56894781003, 2659.52271740553, 2615.9025930681,
2923.69327019152, 2754.76074569658, 2784.59488335761, 2874.24378479002,
2683.41908597168, 2733.83011888159, 2774.1325162997, 2906.41593326865,
2726.06821502751, 2460.21579967528, 2450.8035097605, 2547.39389733175,
2625.60323572861, 2827.94083526683, 2971.92012845614, 3042.90981987278,
2835.00811374845, 2846.98066660519, 2871.21876763166, 2901.99696373824,
2627.47532996657, 2583.75084300313, 2602.68041642846, 2632.8054092953,
2667.85374690972, 2639.10586730146, 2466.95799545022, 2381.06823502402,
2531.32611053776, 2407.14812148706, 2342.75701798463, 2401.73791085847,
2365.50645844524, 2404.50408575777, 2452.57343738519, 2613.15332739214,
2665.50965844576, 2723.8237337447, 2915.09266385617, 2890.17498445896,
2853.6278331055, 2868.1228183545, 2917.07803535669, 2876.59409770233,
2577.82035337979, 2581.91435020803, 2520.20342021937, 2603.37973251208,
2536.03988578365, 2510.83398648802, 2472.80606784857, 2425.51212342113,
2442.02863541673, 2465.73405821711, 2384.42988766816, 2555.51500549788,
2737.77091706275, 2425.00224845814, 2460.17325671183, 2639.16650619329,
2816.37024420397, 2755.69999167982, 2802.64991688288, 2685.12803367301,
2521.77568128564, 2500.99980614696, 2620.41659854805, 2529.25134423133,
2590.14804885984, 2318.80485234464, 2341.88940012276, 2460.21008281205,
2513.70688167177, 2437.71670675479, 2383.29782281743, 2499.36244454453,
2472.98602901478, 2491.10649022417, 2350.1405559119, 2362.78308814045,
2431.3911847573, 2321.15216823049, 2355.74203614213, 2429.60523843166,
2355.61947983433, 2346.3751018515, 2453.82214513707, 2542.98125962684,
2342.43364707529, 2302.17741211575, 2388.93541944219, 2435.41878657221, ....
Sample output from dput for actual observed values:
structure(list(index12 = c(6297.416944, 5406.865556, 4718.355556,
5304.729167, 4968.014722, 5081.130833, 5544.955, 4655.009444,
4269.023056, 4346.588333, 4511.455833, 5102.57, 4818.673333,
4862.343056, 4785.176667, 5385.005278, 6469.080833, 7166.025278,
7010.708333, 511.114167)), .Names = "index12", class = "data.frame", row.names = c(NA,
-20L))
The value of Point is unusual in spite of hour unit data. I think you failed to make a model.
Here is my example:
actual_data <- structure(list(index12 = c(6297.416944, 5406.865556, 4718.355556,
5304.729167, 4968.014722, 5081.130833, 5544.955, 4655.009444,
4269.023056, 4346.588333, 4511.455833, 5102.57, 4818.673333,
4862.343056, 4785.176667, 5385.005278, 6469.080833, 7166.025278,
7010.708333, 511.114167)),
.Names = "index12", class = "data.frame", row.names = c(NA, -20L))
# I suppose that actual_data was taken per hour.
num_actual <- as.numeric(actual_data[,1])
model <- bats(num_actual)
fore_cast <- forecast(model, h=24, level=90)
fore_cast # Point is from 21 to 44 because of length(actual_data)=20 and demanding predictions for the next 24 hours
# Point Forecast Lo 90 Hi 90
# 21 5063.207 2902.187 7224.226
# 22 5108.114 2946.988 7269.241
# :
# 44 5108.114 2944.629 7271.600
# plot() has forecast method. It draws actual_data and prediction, and paints Lo90-Hi90.
plot(fore_cast, main="")