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Hello, I have a question regarding a way to control the appreance of output exported by R when I use capture.output( x, file = "Directory/file.txt") , I get a text file which when I paste to a word file looks like the first table below. The following table has its clumns spaced closely so when I paste it to a word file it looks continuous. Is there any option in R to make the outputs

I tried to bootstrap the correlation between two variables x1 and x2. The resulting distribution has two distinct peaks, how should I interprete it? The original code is attached. Y. C. Tao ---------------- library(boot); my.correl<-function(d, i) cor(d[i,1], d[i,2]) x1<-c(-2.612,-0.7859,-0.5229,-1.246,1.647,1.647,0.1811,-0.07097,0.8711,0.4323,0.1721,2.143,

I wonder if it's possible to run R-functions or other commands automatically by some shell-script in Linux shell. I thought that something like $ R mean(c(1,2)) $ R xy.Rdata would work, but I havent found the right way.

Hi, I have three original curves as follows, n<-seq(20,200,by=10) t<-c(0.1138, 0.1639, 0.2051, 0.2473, 0.2890, 0.3304, 0.3827, 0.4075, 0.4618, 0.4944, 0.5209, 0.5562, 0.5935, 0.6197, 0.6523, 0.6771, 0.6984, 0.7209, 0.7453) es<-c(0.3682, 0.4268, 0.5585, 0.6095, 0.7023, 0.7534, 0.8225, 0.8471, 0.8964, 0.9098, 0.9371, 0.9514, 0.9685, 0.9747, 0.9812, 0.9859, 0.9905, 0.9923, 0.9940)

Hi all, This should be a very simple question for you, whereas it is proving devilish for me. How do I output the STANDARD ERROR of the regression coefficient (i.e., the standard error of b) from a simple linear regression? Consider this data, taken directly from ?lm: 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)

Dear all, is there anyone who can help me extracting p-values from an Anova object from the car library? I can't seem to locate the p-values using str(result) or str(summary(result)) in the example below > A <- factor( rep(1:2,each=3) ) > B <- factor( rep(1:3,times=2) ) > idata <- data.frame(A,B) > fit <- lm( cbind(a1_b1,a1_b2,a1_b3,a2_b1,a2_b2,a2_b3) ? sex,

I have found the use of save( ) and attach( ) when supported by a pair of functions written by my colleague John Miyamoto, move( ) and rm.sv( ) quite useful in managing (1) collections of useful homebrew functions, (2) project workspaces, and (3) "packages" under development. An .Rdata file containing these and other handy functions together with a brief supporting document can be

Thank you for reading. I am trying to get sphericity values, and I understood I need to use mlm, but how do I implement a nested within subject design in mlm? I already read the R newsletter, fox chapter appendix, EZanova, and whatever I could find online. My original ANOVA anova(aov(resp ~ sucrose*citral, random =~1 | subject, data = p12bl, subset = exps==1)) Or anova(aov(resp ~