(statistics) 2-way table normalization - r
I have a table like this.
X X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015
1 SU 103.27 105.2 99.7 106.7 96.7 108.4 88.7 73.67
2 BS 100.17 104.5 97.6 103.6 91.7 106.2 85.5 73.66
3 DG 101.00 102.5 98.9 101.1 91.2 106.2 80.9 75.67
4 IC 97.80 103.4 97.2 102.4 88.4 103.3 85.7 70.00
5 DJ 106.20 103.1 99.1 97.7 90.7 106.2 77.5 74.00
6 GJ 97.47 101.7 98.6 101.2 89.9 105.6 81.7 73.33
7 US 99.80 105.6 98.2 0.0 81.7 103.6 84.3 68.00
8 GG 98.13 105.7 98.6 103.7 92.2 105.2 85.9 73.66
9 GO 96.13 101.2 96.8 101.7 86.4 105.7 78.1 72.66
10 CB 104.20 105.2 101.5 100.3 88.3 106.2 78.8 72.00
11 CN 107.20 95.0 96.1 98.7 88.2 103.7 78.5 71.33
12 GB 98.87 102.0 95.3 100.2 87.2 104.2 78.5 70.33
13 GN 99.57 103.3 95.6 102.6 89.2 103.7 83.2 72.00
14 JB 99.60 96.2 98.2 96.2 86.2 101.7 84.5 71.34
15 JN 93.83 98.6 98.8 95.2 87.2 102.7 83.9 70.33
16 JJ 93.63 101.7 93.2 98.1 0.0 0.0 83.9 71.00
17 SJ 0.00 0.0 0.0 0.0 0.0 106.5 81.9 73.34
This is a test score that took place in some provinces of South Korea in each year.
The boundary of the test score was [0,110] until 2013, but it was changed to [0,100] in 2014.
My objective is to normalize the test score into some boundary or hopely some standardized region.
Maybe, I can first convert the scores among 2008 and 2013 into 100% scale, and subtract column mean and divide by standard deviation of each column to achieve this. But then, that is only standardized in each column.
Is there any possible way to normalize (or standardize) the test score as a whole?
By the way, the test score 0 means there was no test, so it must be ignored in the normalization process. And, this is csv format for your convenience..
,2008,2009,2010,2011,2012,2013,2014,2015
SU,103.27,105.2,99.7,106.7,96.7,108.4,88.7,73.67
BS,100.17,104.5,97.6,103.6,91.7,106.2,85.5,73.66
DG,101,102.5,98.9,101.1,91.2,106.2,80.9,75.67
IC,97.8,103.4,97.2,102.4,88.4,103.3,85.7,70
DJ,106.2,103.1,99.1,97.7,90.7,106.2,77.5,74
GJ,97.47,101.7,98.6,101.2,89.9,105.6,81.7,73.33
US,99.8,105.6,98.2,0,81.7,103.6,84.3,68
GG,98.13,105.7,98.6,103.7,92.2,105.2,85.9,73.66
GO,96.13,101.2,96.8,101.7,86.4,105.7,78.1,72.66
CB,104.2,105.2,101.5,100.3,88.3,106.2,78.8,72
CN,107.2,95,96.1,98.7,88.2,103.7,78.5,71.33
GB,98.87,102,95.3,100.2,87.2,104.2,78.5,70.33
GN,99.57,103.3,95.6,102.6,89.2,103.7,83.2,72
JB,99.6,96.2,98.2,96.2,86.2,101.7,84.5,71.34
JN,93.83,98.6,98.8,95.2,87.2,102.7,83.9,70.33
JJ,93.63,101.7,93.2,98.1,0,0,83.9,71
SJ,0,0,0,0,0,106.5,81.9,73.34
I think the best would probably need be to convert columns 2 to 6 i.e. the ones in the range [0-110] to the range of [0-100]. In this way everything will be in the same scale. In order to do this:
Data:
df <- read.table(header=T, text=' X X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015
1 SU 103.27 105.2 99.7 106.7 96.7 108.4 88.7 73.67
2 BS 100.17 104.5 97.6 103.6 91.7 106.2 85.5 73.66
3 DG 101.00 102.5 98.9 101.1 91.2 106.2 80.9 75.67
4 IC 97.80 103.4 97.2 102.4 88.4 103.3 85.7 70.00
5 DJ 106.20 103.1 99.1 97.7 90.7 106.2 77.5 74.00
6 GJ 97.47 101.7 98.6 101.2 89.9 105.6 81.7 73.33
7 US 99.80 105.6 98.2 0.0 81.7 103.6 84.3 68.00
8 GG 98.13 105.7 98.6 103.7 92.2 105.2 85.9 73.66
9 GO 96.13 101.2 96.8 101.7 86.4 105.7 78.1 72.66
10 CB 104.20 105.2 101.5 100.3 88.3 106.2 78.8 72.00
11 CN 107.20 95.0 96.1 98.7 88.2 103.7 78.5 71.33
12 GB 98.87 102.0 95.3 100.2 87.2 104.2 78.5 70.33
13 GN 99.57 103.3 95.6 102.6 89.2 103.7 83.2 72.00
14 JB 99.60 96.2 98.2 96.2 86.2 101.7 84.5 71.34
15 JN 93.83 98.6 98.8 95.2 87.2 102.7 83.9 70.33
16 JJ 93.63 101.7 93.2 98.1 0.0 0.0 83.9 71.00
17 SJ 0.00 0.0 0.0 0.0 0.0 106.5 81.9 73.34')
You could do:
df[2:6] <- lapply(df[2:6], function(x) {
x / 110 * 100
})
Essentially you divide by 120 which is the max in [0-110] in order to convert to the range between [0-1] and then multiply by 100 to convert that in the range between [0-100].
Output:
> df
X X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015
1 SU 93.88182 95.63636 90.63636 97.00000 87.90909 108.4 88.7 73.67
2 BS 91.06364 95.00000 88.72727 94.18182 83.36364 106.2 85.5 73.66
3 DG 91.81818 93.18182 89.90909 91.90909 82.90909 106.2 80.9 75.67
4 IC 88.90909 94.00000 88.36364 93.09091 80.36364 103.3 85.7 70.00
5 DJ 96.54545 93.72727 90.09091 88.81818 82.45455 106.2 77.5 74.00
6 GJ 88.60909 92.45455 89.63636 92.00000 81.72727 105.6 81.7 73.33
7 US 90.72727 96.00000 89.27273 0.00000 74.27273 103.6 84.3 68.00
8 GG 89.20909 96.09091 89.63636 94.27273 83.81818 105.2 85.9 73.66
9 GO 87.39091 92.00000 88.00000 92.45455 78.54545 105.7 78.1 72.66
10 CB 94.72727 95.63636 92.27273 91.18182 80.27273 106.2 78.8 72.00
11 CN 97.45455 86.36364 87.36364 89.72727 80.18182 103.7 78.5 71.33
12 GB 89.88182 92.72727 86.63636 91.09091 79.27273 104.2 78.5 70.33
13 GN 90.51818 93.90909 86.90909 93.27273 81.09091 103.7 83.2 72.00
14 JB 90.54545 87.45455 89.27273 87.45455 78.36364 101.7 84.5 71.34
15 JN 85.30000 89.63636 89.81818 86.54545 79.27273 102.7 83.9 70.33
16 JJ 85.11818 92.45455 84.72727 89.18182 0.00000 0.0 83.9 71.00
17 SJ 0.00000 0.00000 0.00000 0.00000 0.00000 106.5 81.9 73.34
And now you can compare between the years. Also, as you will notice zeros will remain zeros.
Related
How can I organise and move row of data based on label matches?
I have raw data shown below. I'm trying to move a row of data that corresponds to a label it matches to a new location in the dataframe. dat<-read.table(text='RowLabels col1 col2 col3 col4 col5 col6 L 24363.7 25944.9 25646.1 25335.4 23564.2 25411.5 610 411.4 439 437.3 436.9 420.7 516.9 1 86.4 113.9 103.5 113.5 80.3 129 2 102.1 99.5 96.3 100.4 99.5 86 3 109.7 102.2 100.2 112.9 92.3 123.8 4 88.9 87.1 103.6 102.5 93.6 134.1 5 -50.3 -40.2 -72.3 -61.4 -27 -22.7 6 -35.3 -9.3 25.3 -0.3 15.6 -27.3 7 109.9 85.8 80.7 69.3 66.4 94 181920 652.9 729.2 652.1 689.1 612.5 738.4 1 104.3 107.3 103.5 104.2 98.3 110.1 2 103.6 102.6 100.1 103.2 88.8 117.7 3 53.5 99.1 46.7 70.3 53.9 32.5 4 93.5 107.2 98.3 99.3 97.3 121.1 5 96.8 109.3 104 102.2 98.7 112.9 6 103.6 96.9 104.7 104.4 91.5 137.7 7 97.6 106.8 94.8 105.5 84 106.4 181930 732.1 709.6 725.8 729.5 554.5 873.1 1 118.4 98.8 102.3 102 101.9 115.8 2 96.7 103.3 104.6 105.2 81.9 128.7 3 96 98.2 99.4 97.9 69.8 120.6 4 100.7 101 103.6 106.6 59.6 136.2 5 106.1 103.4 104.7 104.8 76.1 131.8 6 105 102.1 103 108.3 81 124.7 7 109.2 102.8 108.2 104.7 84.2 115.3 N 3836.4 4395.8 4227.3 4567.4 4009.9 4434.6 610 88.1 96.3 99.6 92 90 137.6 1 88.1 96.3 99.6 92 90 137.6 181920 113.1 100.6 106.5 104.2 87.3 108.2 1 113.1 100.6 106.5 104.2 87.3 108.2 181930 111.3 99.1 104.5 115.5 103.6 118.8 1 111.3 99.1 104.5 115.5 103.6 118.8 ',header=TRUE) I want to match the values of the three N-prefix labels: 610, 181920 and 181930 with its corresponding L-prefix labels. Basically move that row of data into the L-prefix as a new row, labeled 0 or 8 for example. So, the result for label, 610 would look like: RowLabels col1 col2 col3 col4 col5 col6 610 411.4 439 437.3 436.9 420.7 516.9 1 86.4 113.9 103.5 113.5 80.3 129 2 102.1 99.5 96.3 100.4 99.5 86 3 109.7 102.2 100.2 112.9 92.3 123.8 4 88.9 87.1 103.6 102.5 93.6 134.1 5 -50.3 -40.2 -72.3 -61.4 -27 -22.7 6 -35.3 -9.3 25.3 -0.3 15.6 -27.3 7 109.9 85.8 80.7 69.3 66.4 94 8 88.1 96.3 99.6 92 90 137.6 Is this possible? I tried searching and I found some resources pointing toward dplyr or tidyr or aggregate. But I can't find a good example that matches my case. How to combine rows based on unique values in R? and Aggregate rows by shared values in a variable
library(dplyr)
library(zoo)
df <- dat %>%
filter(grepl("^\\d+$",RowLabels)) %>%
mutate(RowLabels_temp = ifelse(grepl("^\\d{3,}$",RowLabels), as.numeric(as.character(RowLabels)), NA)) %>%
na.locf() %>%
select(-RowLabels) %>%
distinct() %>%
group_by(RowLabels_temp) %>%
mutate(RowLabels_indexed = row_number()-1) %>%
arrange(RowLabels_temp, RowLabels_indexed) %>%
mutate(RowLabels_indexed = ifelse(RowLabels_indexed==0, RowLabels_temp, RowLabels_indexed)) %>%
rename(RowLabels=RowLabels_indexed) %>%
data.frame()
df <- df %>% select(-RowLabels_temp)
df
Output is
col1 col2 col3 col4 col5 col6 RowLabels
1 411.4 439.0 437.3 436.9 420.7 516.9 610
2 86.4 113.9 103.5 113.5 80.3 129.0 1
3 102.1 99.5 96.3 100.4 99.5 86.0 2
4 109.7 102.2 100.2 112.9 92.3 123.8 3
5 88.9 87.1 103.6 102.5 93.6 134.1 4
6 -50.3 -40.2 -72.3 -61.4 -27.0 -22.7 5
7 -35.3 -9.3 25.3 -0.3 15.6 -27.3 6
8 109.9 85.8 80.7 69.3 66.4 94.0 7
9 88.1 96.3 99.6 92.0 90.0 137.6 8
...
It sounds like you want to use the match() function, for example: target<-c(the values of your target order) df<-df[match(target, df$column_to_reorder),]
as.Date conversion returns NA
I am using this data. When I want to define the variable as.Date() I am getting NA.
This is the code I am using. Can someone please advise what I am doing wrong?
dataf <- read.csv("DB.csv")
dataf$Date <- as.Date(dataf$Date, format = "%b-%Y")
str(dataf)
'data.frame': 55 obs. of 9 variables:
$ Date : Date, format: NA NA ...
$ Sydney : num 85.3 88.2 87 84.4 84.2 84.8 83.2 82.6 81.4 81.8 ...
$ Melbourne: num 60.7 62.1 60.8 60.9 60.9 62.4 62.5 63.2 63.1 64 ...
$ Brisbane : num 64.2 69.4 70.7 71.7 71.2 72 72.6 73.3 73.6 75 ...
$ Adelaide : num 62.2 63.9 64.8 65.9 67.1 68.6 68.6 69.3 70 71.6 ...
$ Perth : num 48.3 50.6 52.5 53.7 54.7 57.1 59.4 62.6 65.2 70 ...
$ Hobart : num 61.2 66.5 68.7 71.8 72.3 74.6 75.8 76.9 76.7 79.1 ...
$ Darwin : num 40.5 43.3 45.5 45.2 46.8 49.7 53.6 54.7 56.1 60.2 ...
$ Canberra : num 68.3 70.9 69.9 70.1 68.6 69.7 70.3 69.9 70.1 71.7 ...
In addition to the good suggestions in the comments, you should try lubridate::parse_date_time" which can handle incomplete dates
as.Date("01-2017", format="%m-%Y")
# [1] NA
as.POSIXct("01-2017", format="%m-%Y")
# [1] NA
as.POSIXlt("01-2017", format="%m-%Y")
# [1] NA
library(lubridate)
parse_date_time("01-2017", "my")
# [1] "2017-01-01 UTC"
Chrome: SVG container not rescaling responsively
I have an SVG that is effectively being used as a 'mask'; it's displayed over the top of another div with a background image so that the image peeks through the unfilled areas of the SVG. The SVG itself is responsive to the height of the document (rather than the width). This works fine so far.
However, I've just been made aware that if you resize the (Chrome) browser, the background image overflows out of the bounds of the masking SVG; however, if you refresh the resized page, everything appears as expected - it only occurs on resize, and only in Chrome (oh, and Opera too, apparently). Works as expected in FF and Safari.
I've included a demo here (and a jsFiddle) with an inline SVG, however it doesn't seem to matter if it's inline or with an <img /> tag - the results are the same.
It seems to be somehow related to the containing element; if I open up the inspector and set the containing element's padding to 0 after it goes screwy, then it seems to figure itself out and suddenly appear as expected; however if I include that rule in the loaded CSS then it makes no difference. I even tried triggering similar CSS properties on page resize via Javascript, but it hasn't made any difference.
Am I missing something, or have I stumbled across a bug?
#splash {
position: relative;
height: 100vh;
padding: 3rem;
overflow: hidden;
display: flex;
-webkit-box-align: center;
align-items: center;
background-color: #DDDDDD;
}
#logowrapper {
position: relative;
width: auto;
height: 60%;
margin: auto;
}
#logowrapper .kitten {
position: absolute;
top: 0;
left: 0;
bottom: 0;
right: 0;
background-image: url('http://placekitten.com/200/300');
background-size: cover;
}
#logowrapper svg {
position: relative;
width: auto;
height: 100%;
z-index: 4;
}
<div id="splash">
<div id="logowrapper">
<div class="kitten"></div>
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0 0 200 300" preserveAspectRatio="xMinYMin meet">
<defs/>
<g>
<path stroke="none" fill="#DDDDDD" d="M110.95 215.1 Q100 225.6 100 240.7 100 256.25 110.75 266.85 121.45 277.5 137 277.5 153.9 277.5 165.45 267.4 177 257.35 177 242.5 177 226.85 166.7 216.1 155.6 204.6 137.5 204.6 121.85 204.6 110.95 215.1 M82.9 206.15 L82.2 206.05 80.3 206.05 Q75.15 206.05 71.55 207.25 66.35 208.95 66.35 212.7 66.35 215.65 67.75 216.9 L69.25 218.45 Q69.25 220.6 67.05 223.4 64.85 226.1 64.05 226.1 L63.8 226.1 Q62.45 225.9 60.35 223.3 58.25 220.75 58.25 218.4 58.25 217.8 59.6 217.1 60.95 216.3 60.95 214.7 L60.85 213.3 Q60.35 210.15 57.05 208.5 53.7 206.9 50.15 206.9 L32.8 206.9 27.25 207.75 Q21.85 209.3 21.85 213.1 21.85 214.8 23.35 216.2 24.85 217.8 28.4 219.3 29.9 219.9 35.1 226.2 40.3 232.5 44.5 239.15 45.2 240.05 45.4 242.35 L45.6 248.15 45.4 255.5 45 261.5 Q45 263.1 42.8 264.65 38.2 267.8 38.2 269.6 38.2 274.8 45.2 275.9 L58.55 276.5 61.45 276.5 64.35 276.6 Q69.45 276.6 72.2 275.6 75.85 274.1 77.25 270.45 L77.45 269.1 Q77.45 267.2 75.15 265.6 70.45 262.25 70.45 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188.35 L119.6 188.2 124.9 188.05 129.2 188.2 133.15 188.35 Q139 188.35 142.5 185.45 145.95 182.6 145.95 177.7 145.95 173.8 142.8 171.8 139.6 169.85 139.6 169.4 L142 166.2 Q143.1 164.4 143.1 162.15 143.1 157.75 139.35 155.9 136.65 154.55 131.8 154.55 L127.55 154.65 121.75 154.75 118.8 154.65 114.9 154.55 Q113.4 154.55 112.45 155.25 111.5 155.95 111.5 157 111.5 157.75 111.95 158.35 M106.65 123.3 L103.7 123.4 97.65 123.4 95.55 123.65 Q95.05 123.9 95.05 124.6 95.05 125.15 95.75 125.45 96.4 125.7 96.6 126 97.15 127.2 97.15 131.75 L97.05 134.45 96.8 136.4 Q96.6 137.2 95.9 137.6 95.2 137.95 95.2 138.45 95.2 139.45 96.45 139.45 L106.35 139.45 108.1 139.65 109.05 139.7 Q109.8 139.7 110.55 137.9 L111.2 135.45 110.9 134.3 Q110.55 133.9 110.05 133.9 109.7 133.9 108.65 135.5 107.5 137.1 104.5 137.1 102.9 137.1 102.55 136.65 102.25 136.15 102.25 133.95 102.25 133 102.4 132.65 102.6 132.35 103.15 132.35 104.35 132.35 104.65 133.55 104.9 134.75 105.45 134.75 106.15 134.75 106.6 133.75 107 132.7 107 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</g>
</svg>
</div>
</div>
If you want to use a responsive inline SVG in your HTML, the SVG shouldn't have width and height attributes.
Update:
Maybe It's a bug on Blink (or Webkit). And I tried to use a redraw hack.
https://jsfiddle.net/pbg1g4uv/2/
#logowrapper svg {
position: relative;
width: auto;
height: 100%;
z-index: 4;
animation: redraw 1s infinite;
}
#keyframes redraw {
from { min-width: 1px; }
to { min-width: 2px; }
}
Animating SVG path with a clipPath using CSS
I thought I was doing something pretty trivial; animating a masked shape within an SVG, but it has utterly confounded me.
I have a relatively simple setup: an SVG with a defined clipPath and a path that uses said mask. Statically, this works exactly as expected - the clipPath masks the pattern I'm using. However, I was intending to animate the path so that it swoops in nicely, creating a nice text effect:
The first issue I encountered was that I couldn't use left or top in CSS to manipulate the position of path. I found a thread here that suggested using transform: translate(100px, 100px); which ostensibly seems to work. However, as soon as I move my path, the actual clipMask moves with it so that the whole thing appears off-centre.
To an extent I can kinda see how this might make sense, but coming from a Flash background I'm used to my masks staying still while I move the masked element.
I've set up a jsFiddle to illustrate the issue, and here's a code snippet:
body {
font-family: Trebuchet MS, san-serif;
}
#helvetica {
width: 100%;
background-color: pink;
}
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left: -300px;
/*transform: translate(-300px, 0);*/
}
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</svg>
</div>
<p>
Uncomment the <code>transform</code> line in the CSS to see the effect - the mask moves <em>with</em> the masked shape.
</p>
Is there another way to achieve the same effect? Note that this will be placed over a photographic image, so an animated GIF isn't going to cut it, and it must be scalable without loss of quality (hence, SVG).
If you don't want the clip to move, all you have to do is put it on something that doesn't move.
body {
font-family: Trebuchet MS, san-serif;
}
#helvetica {
width: 100%;
background-color: pink;
}
#helvetica svg path#pattern {
left: -300px;
transform: translate(-300px, 0);
}
<div id="helvetica">
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="550" height="80" viewbox="0 0 550 80">
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</svg>
</div>
How to create a plot consisting of multiple residuals?
How can I make a residual plot according to the following (what are y_hat and e here)? Is this a form of residual plot as well? beeflm=lm(PBE ~ CBE + PPO + CPO + PFO +DINC + CFO+RDINC+RFP+YEAR, data = beef) summary(beeflm) qqnorm(residuals(beeflm)) #plot(beeflm) #in manuals I have seen they use this but it gives me multiple plot or is this one correct? plot(beeflm$residuals,beeflm$fitted.values) I know through the comments that plot(beeflm,which=1) is correct but according to the stated question I should use matplot but I receive the following error: matplot(beeflm,which=1, + main = "Beef: residual plot", + ylab = expression(e[i]), # only 1st is taken + xlab = expression(hat(y[i]))) Error in xy.coords(x, y, xlabel, ylabel, log = log) : (list) object cannot be coerced to type 'double' And when I use plot I receive the following error: plot(beeflm,which=1,main="Beef: residual plot",ylab = expression(e[i]),xlab = expression(hat(y[i]))) Error in plot.default(yh, r, xlab = l.fit, ylab = "Residuals", main = main, : formal argument "xlab" matched by multiple actual arguments Also do you know what does the following mean? Any example for illustrating this (or external link)? Beef data is like the following: Here's the beef data.frame: YEAR PBE CBE PPO CPO PFO DINC CFO RDINC RFP 1 1925 59.7 58.6 60.5 65.8 65.8 51.4 90.9 68.5 877 2 1926 59.7 59.4 63.3 63.3 68.0 52.6 92.1 69.6 899 3 1927 63.0 53.7 59.9 66.8 65.5 52.1 90.9 70.2 883 4 1928 71.0 48.1 56.3 69.9 64.8 52.7 90.9 71.9 884 5 1929 71.0 49.0 55.0 68.7 65.6 55.1 91.1 75.2 895 6 1930 74.2 48.2 59.6 66.1 62.4 48.8 90.7 68.3 874 7 1931 72.1 47.9 57.0 67.4 51.4 41.5 90.0 64.0 791 8 1932 79.0 46.0 49.5 69.7 42.8 31.4 87.8 53.9 733 9 1933 73.1 50.8 47.3 68.7 41.6 29.4 88.0 53.2 752 10 1934 70.2 55.2 56.6 62.2 46.4 33.2 89.1 58.0 811 11 1935 82.2 52.2 73.9 47.7 49.7 37.0 87.3 63.2 847 12 1936 68.4 57.3 64.4 54.4 50.1 41.8 90.5 70.5 845 13 1937 73.0 54.4 62.2 55.0 52.1 44.5 90.4 72.5 849 14 1938 70.2 53.6 59.9 57.4 48.4 40.8 90.6 67.8 803 15 1939 67.8 53.9 51.0 63.9 47.1 43.5 93.8 73.2 793 16 1940 63.4 54.2 41.5 72.4 47.8 46.5 95.5 77.6 798 17 1941 56.0 60.0 43.9 67.4 52.2 56.3 97.5 89.5 830
Use plot(beeflm, which=1) to get the plot between residuals and fitted values.
require(graphics)
## Annette Dobson (1990) "An Introduction to Generalized Linear Models".
## Page 9: Plant Weight Data.
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
plot(lm.D9, which=1)
Edited
You can use matplot as given below:
matplot(
x = lm.D9$fitted.values
, y = lm.D9$resid
)
An example illustrating this using the mtcars data: fit <- lm(mpg ~ ., data=mtcars) plot(x=fitted(fit), y=residuals(fit)) and par(mfrow=c(3,4)) # or 'layout(matrix(1:12, nrow=3, byrow=TRUE))' for (coeff in colnames(mtcars)[-1]) plot(x=mtcars[, coeff], residuals(fit), xlab=coeff, ylab=expression(e[i]))