search for: respmat

Hi, I have managed to format my data into a single datframe consisting of two AsIs response and predictor dataframes in order to supply the plsr command of the pls package for principal components analysis. When I execute the command, however, I get this error: > fiber1 <- plsr(respmat ~ predmat, ncomp=1, data=inputmat,validation="LOO") Error in model.frame.default(formula = respmat ~ predmat, data = inputmat) : invalid type (list) for variable ''respmat'' I happen to have a lot of NAs in some of the columns. Is that the problem? Any input will be g...

...t to specify file name to save item characterstic curve by passing it as external parameter to the R batch script. The following is the code I have written for this. *R Script:* library(ltm) cmd_args = commandArgs(); for (arg in cmd_args) cat(" ", arg, "\n", sep="") respmat <- read.table("C:\\rphp\\responsedata.txt") fit3pl <- tpm(respmat) cat(" ", arg, "\n", sep="") b <- c("C:\\rphp\\",arg) png(file=b, bg="transparent") plot(fit3pl,items=c,lwd=3) dev.off() rm(respmat,fit3pl,b) q() Could you please...

Hello all, It seems that the GeneMeta passage returns NA in the respective row if any gene in the data sets to be synthesised are missing. Do you know of a way to overcome this problem? I tried using the 'impute' package to fill-in the missing values, but R crashes if 'impute' and 'GeneMeta' packages are used together. I have asked a separate question for that. Thanks

Dear List, I find Effects package very useful, but I believe I have found a bug in allEffects function. Please consider the following code: test <- data.frame(tries= round(runif(40, 5, 300)), tra = gl(4, 10, labels = c("V", "D", "C", "L")), prop= runif(40, 0, 1)) test$success <- round(with(test, tries*prop)) test$prop <- with(test,

...ing placed oddly in memory. If I unload and reload the .dll it works again the first time. It does the same if I copy the compiled .dll over to my Windows XP machine. Thank you for any help, Brian Habing habing at stat.sc.edu The Fortran subroutine beings with: subroutine ccprox(nexmn,nitem,respmat2,covmatr,covmatt, $ cormatr,cormatt) !ccccc This subroutine will calculate all the pairwise !ccccc conditional covariances. An ending r means for !ccccc rest score, an ending t means for total score. parameter (maxitem=100,maxexmn=10000,maxcats=10,ncells=1001) !ccccc ncells...