similar to: Variance of a single number

Dear all, I am trying to create a web interface using Perl-CGI to call R plots and to display them. The following codes works perfectly fine when I copy and paste into the console directly or if I save it into script.file and then R --no-save < script.file producing the graphs. jpeg("graph.jpeg", width=400, height=400) plot(rnorm(100)) dev.off() Now, I put the line system("R

Just out of curiosity, what is the difference between the terms for package and library ? Why are we loading a package with the library() command ? If this is a case of RTFM, I would be happy to do so if pointed in the right direction. I have searched the FAQ and mail archives and only came up with http://tolstoy.newcastle.edu.au/R/help/05/02/12162.html but this still does not explain what is

Could some kindly tell me if I am supposed to be getting the same test statistic value with var.equal=TRUE and var.equal=FALSE in t.test ? set.seed(1066) x1 <- rnorm(50) x2 <- rnorm(50) t.test(x1, x2, var.equal=FALSE)$statistic # 0.5989774 t.test(x1, x2, var.equal=TRUE)$statistic # 0.5989774 ??? Here are my own calculations that shows that perhaps the result when var.equal=TRUE is

Dear all, I am trying to compile the package e1071 (version 1.3-11) with R CMD INSTALL. I tried with R 1.7.0 on Redhat Linux 2.4.7-10 and R 1.6.2 on Linux 2.4.9-34smp but keep getting the same error message during configure : WARNING: g++ 2.96 cannot reliably be used with this package. Please use a different compiler. Can anyone help me with this or at least point me in the right direction ?

I am trying to write a wrapper for the last example in help(cv.glm) that deals with leave-one-out-cross-validation (LOOCV) for a logistic model. This wrapper will be used as part of a bigger program. Here is my wrapper funtion : logistic.LOOCV.err <- function( formu=NULL, data=NULL ){ cost.fn <- function(cl, pred) mean( abs(cl-pred) > 0.5 ) glmfit <- glm(

Dear all, A few weeks ago I asked about X11() availability using CGI-perl. The general advice was to use bitmap which requires ghostscript (Xvnc and Xvbf were the other alternatives). My system administrator got around to installing Aladin Ghostscript 6.0 and the setting the R_GSCMD environment variable. Other system specification is given below. But now I have a new problem that says that font

Sorry if this is a question more on regular expressions. I am dealing with several files which have been badly named. For example the files are given either the extensions txt, TXT or Txt. I wish to select all those files ending with 'txt' ignoring case. Here is how I would do it in bash (Redhat FC2) : touch a1.txt a2.TXT a3.Txt txt.control TXT.control ls -1 | grep -i

I am comparing two different algorithms in terms of speed and memory usage. I can calculate the processing time with proc.time() as follows but am not sure how to calculate the memory usage. ptm <- proc.time() x <- rnorm(1000000) proc.time() - ptm I would like to be within R itself since I will test the algorithm several hundred times and in batch mode. So manually looking up

Forgive me for I do not fully comprehend the idea of classes and methods but I was wondering if someone could help explain why the function args () behaves the way it does. Why does args(cut) show the simplified version instead of the more complete one as in help("cut"). This is true for few other functions (e.g. plot, rep). > args(cut) function (x, ...) Sometime I can get

Hello, I am trying to use self created functions in other scripts than the one where they are stored. For the moment I am using the following structure of commands to do that: 1. Load the text file with the functions in the current script: x=parse("path") 2. transform the tex in a function: f1=eval(x[1]), f2=eval(x[2]) if more than one function is stored in the text file 3. use the

Hi there, Suppose mu is constant, and error is normally distributed with mean 0 and fixed variance s. I need to find a statistics that: Y_i = mu + beta1* I1_i beta2*I2_i + beta3*I1_i*I2_i + +error, where I_i is 1 Y_i is from group A, and 0 if Y_i is from group B. It is large when beta1=beta2=0 It is small when beta1 and/or beta2 is not equal to 0 How can I find it by R? Thank you very much

Hello guys, I am wondering the default way of transferring arguments in R. Is it by value or by ref in default case, or could that be changed explicitly? Cheers, Xiaofan --- Xiaofan Li Department of Applied Mathematics and Theoretical Physics University of Cambridge

I have a vector with about 100.000 values representing a quite regular function (sinusoid like). I would like to find all local maxima of this function (should be about 4000). Is there a native routine for R? Thanks in advance Eryk. -- _|_ \|/ \|/ Eryk Witold Wolski tel :0049-(0)30-8413-1543 w w ?v? 'v? \'v'/ MPI Moleculare Genetik fax :0049-(0)30-8413-1139 |

I am trying to replicate the first example from stepAIC from the MASS package with my own dataset but am running into error. If someone can point where I have gone wrong, I would appreciate it very much. Here is an example : set.seed(1) df <- data.frame( x1=rnorm(1000), x2=rnorm(1000), x3=rnorm(1000) ) df$y <- 0.5*df$x1 + rnorm(1000, mean=8, sd=0.5) # pairs(df); head(df) lo <-

You are using a method that needs to estimate the covariance matrix of all the variables. If you have 80 variables, there are (80+1)*80/2 = 3240 variances and covariances to estimate. How many data points do you think you need to do that? Some people assume the covariance matrix is diagonal (i.e., assuming all the variables are uncorrelated). Even then you still have 80 variances to estimate.

Hi all, If the question below as been answered before I apologize for the posting. I would like to get the frequencies of occurrence of all values in a given variable in a multivariate dataset. In short for each variable (or field) a summary of values contained with in a value:frequency pair, there can be many such pairs for a given variable. I would like to do the same for several such variables.

Hi, I calculating the output of a function when applied to pairs of row from a single matrix or dataframe similar to how cor() and pairs() work. This is the code that I have been using: pairwise.apply <- function(x, FUN, ...){ n <- nrow(x) r <- rownames(x) output <- matrix(NA, nc=n, nr=n, dimnames=list(r, r)) for(i in 1:n){ for(j

I am currently plotting a graph with the function coplot() conditional on two factors which gives me 36 sub-panels. I have a few questions in general about changing the size of the graph. My question follows : a) I have a fair bit of text to put on the margin sides using mtext(). What is the best way to shrink the whole graph to say 80 - 90% so that I can include a bit more words. b) Since I am

Dear all, I used the glm.nb with the default values from the MASS package to run a negative binomial regression. Here is a simple example: set.seed(123) y <- c( rep(0, 30), rpois(70, lambda=2) ) smoke <- factor( sample( c("NO", "YES"), 100, replace=T ) ) height <- c( rnorm(30, mean=100, sd=20), rnorm(70, mean=150, sd=20) ) fit <- glm.nb( y

Hi, I have a matrix with column names starting with a character in [0-9]. After some matrix operations (e.g. copy to another matrix), R seems to add a character 'X' in front of the column name. Is this a normal default behaviour of R? Why has it got this behaviour? Can it be changed? What would be the side effect? Thank you. Regards, Gilbert [[alternative HTML version deleted]]