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I am new to R programming and had a requirement to create a zero byte/tag/touch file on Unix server using R.
Is it possible to create a file on Unix using R?
You can create an empty data frame and write that to disk:
x <- data.frame()
write.table(x, file='empty', col.names=FALSE)
Result:
-rw-rw-r--. 1 matt matt 0 May 28 20:29 empty
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I want to run an estimation assuming that my variables are distributed according to the Dirichlet distribution. To do so, I need to use the cdf function. For all the distributions in R, there are the respective r,p and d functions that produce random variables, pdf and cdf.
Nevertheless, for the Dirichlet, I can only find the random number generator and the pdf.
Is there a similar package for R that gives the cdf?
Many thanks,
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I want to find a list of symbols specials in R, for exemple:
\042
\044
\136
\305
\341
Where is it, please?
Acctualy, i want find the code of symbol ∈ .
I'm unfamiliar with R, but this website helps me with escape symbols. Your posted character, ∈, is \u2208 .
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I am trying to find out how many combinations are possible for 000 through to FFF under hex format? thanks
There are 16 choices for each of the 3 digits, so:
16*16*16 = 4096
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Is there a package in R that allows me to plot multiply time series next to each other 3D?
Like in the following examples:
http://farm6.staticflickr.com/5142/5619005462_5eab3c8cdd_b.jpg
http://synoptic.weaintplastic.com/
Thanks
Have you checked out chartSeries3d0 from the quantmod package?
Here's an example I found on quantmod.com:
library(quantmod)
source("http://www.quantmod.com/examples/chartSeries3d/chartSeries3d.alpha.R")
getSymbols("DGS1MO;DGS3MO;DGS6MO;DGS1;DGS2;DGS3;DGS5;DGS7;DGS10;DGS20;DGS30",src="FRED")
TR <- merge(DGS1MO,DGS3MO,DGS6MO,DGS1,DGS2,DGS3,DGS5,DGS7,DGS10,DGS20,DGS30, all=FALSE)
colnames(TR) <- c("1mo","3mo","6mo","1yr","2yr","3yr","5yr","7yr","10yr","20yr","30yr")
TR <- na.locf(TR)
chartSeries3d0(TR["2011"])
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Is there any scripting language function (like in python or bash) that samples from a zipf-like distribution, for exponent 0<a<=1. Zipf-like distribution p(a) can be found, here.
PS: I am aware of existence of numpy function that can generate zipf samples, but it's only for a >1.