similar to: Accessing coefficient values in linear regression

Dear R users, Can anyone tell me why I might get the error message "the array index is greater than the upper bound for t" in WinBUGS ? t is a vector I have defined. I have checked repeatedly that the array index for t does match with the upper bound till which the loop is run. I am facing this problem while calling the R2WinBUGS package and both in just WinBUGS as

I am running a program which has an output containing four vectors named meanfevs, meanfevns, pfevs, pfevns. I wish to return all four and be able to access them later. I used the command return(list(a=meanfevs,b=meanfevns,c=pfevs,d=pfevns)) it did give me the ouput. However the values did not get stored in the vectors a,b,c and d and i am not being able to access them later by just calling

Hi I am trying to install R-igraph, but when I issue the command : install.packages("igraph", lib="~/.R/library") in the R session, I get the following error: Warning in install.packages("igraph", lib = "~/.R/library") : 'lib = "~/.R/library"' is not writable Error in install.packages("igraph", lib =

Re: Heteroscedasticity and mgcv. (Collin Lynch) The GAMLSS package can model heterogeneity in the scale parameter (e.g. standard deviastion) [and also heterogeity in skewness and kurtosis parameters].of the response variable distribution. For parametric models a generalized likelihood ratio test can be used to test whether the heterogeity is needed. Alternatively a generalized Akaike

Hi, I need some answers regarding to R. In K-means clustering ,for K=2, How can I find the members of each cluster and What are the coordinates for the cluster centers? Please send me a reply soon. Thank You Sent from Windows Mail [[alternative HTML version deleted]]

Hi, I'm very new to working with sparse matrices and would like to know how I can column permute a sparse matrix. Here is a small example: > M1 <- > spMatrix(nrow=5,ncol=6,i=sample(5,15,replace=TRUE),j=sample(6,15,replace=TRUE),x=round_any(rnorm(15,2),0.001)) > M1 5 x 6 sparse Matrix of class "dgTMatrix" [1,] 2.983 . 1.656 5.003 . . [2,] .

I have just compiled and installed R-patched on a Sparc 20 running Solaris 2.5.1. The compilation and installation went fine except for the message: Bare word found where operator expected at /usr/src/R/R-patched/share/perl/R/Rdconv.pm line 1491, near "$txtout txt_header" (Missing operator before txt_header?) I get similar messages for lines 1390, 1405, 1420, and 1448 in Rdconv.pm.

Full_Name: Henrik Bengtsson Version: 1.3.1 OS: Sun Solaris 8 Submission from: (NULL) (130.235.3.49) I have been trying to install [R] v1.3.1 locally on a Sun Solaris 8 machine and I ran into the (already known) perl problems that express theselves as: Bare word found where operator expected at /usr/matcent/hb/R/R-1.3.1/share/perl/R/Rdconv.pm line 1390, near "$txtout mywrap"

Summary: Any user can gain root privileges on a Intel Linux system with suidperl 5.003 (having the suid bit, of course) even if "SUIDBUF" and "two suidperl security patches" have been applied. Non-Intel / non-Linux platforms may be affected as well. Quick fix: chmod u-s /usr/bin/sperl5.003 (what else?) Details: There is a nasty bug in mess() (util.c): it is possible to

Hi all, I'm wanting to be able to find and store the z-score of coxph below: - modz=coxph(Surv(TSURV,STATUS)~RAGE+DAGE+REG_WTIME_M+CLD_ISCH+POLY_VS, data=kidneyT,method="breslow") I know summary(modz) will give me this, but how do i extract the standard error or z-score values in a similar way to obtaining the coefficients by coef(modz) ? I think it must be something to do with

Hi, I am trying to find m breakpoints of a linear regression model. I used the segmented package. It works fine for small number of predicators and breakpoints.(3 r.v. 3 points). However, my model has 14 variables it even would not work even for just one breakpoints!. The error message is always estimated breakpoints are out of range. Since my problem is time related problem. So I

When I installed R 1.2.2 on a Sparc 20 running Solaris 2.5.1 and when I install a package, I get the messages: Bare word found where operator expected at /usr/local/lib/R/share/perl/R/Rdconv.pm line 1390, near "$txtout mywrap" (Missing operator before mywrap?) Bare word found where operator expected at /usr/local/lib/R/share/perl/R/Rdconv.pm line 1405, near "$txtout

I received some large data sets in Minitab Portable Worksheet (.mtp) format and wanted to read them into R. Here is a _first cut_ at a perl script that transforms .mtp files into something that can be read by R. Comments, bug-fixes, enhancements and extensions are welcome. #!/usr/bin/perl # Convert a Minitab Portable Worksheet to an R (or S-PLUS) list structure # $Id: mtp2R.pl,v 1.1 1998/01/16

Dear All: Could you please tell me how I can draw figure formatted like figure 4.18 of MASS (4th) with the attached data set? Thanks Zhongming Yang --------------------------------- -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: sample.txt Url: https://stat.ethz.ch/pipermail/r-help/attachments/20050316/abfdb85e/sample.txt

R 2.2.0 windows XP How can I perform a regression analyses using a vector of means, a variance-covariance matrix? I looked at the help screen for lm and did not see any option for using the afore mentioned structures as input to lm. Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC, University of Maryland School of Medicine Claude D.

This is a function I coded a few years ago to calculate a confidence interval for a coefficient of variation. The code is based on a paper by Mark Vangel in The American Statistician. I have not used the function much, but it could be useful for comparing cv's from different groups. Kevin Wright confint.cv <- function(x,alpha=.05, method="modmckay"){ # Calculate the

Dear Rers, I have threes series, x, y, z and I want to fit a model z ~ x + y. First of all, I fit a lm. I found the residuals are correlated, by looking at the acf() and pacf(). Then I tried to fit a gls model allowing residuals to be correlated (correlation = corARMA(p=5, q=1)): y.na <- as.data.frame(y[complete.cases(y),]) y.gls <- gls(z ~ x + y, data = y.na, correlation=corARMA(p=5,

Hi there Within sampleSelection, I'm trying to calculate the marginal effects for variables that are present in both the selection and outcome models. For example, age might have a positive effect on probability of selection, but then a negative effect on the outcome variable. i.e. Model<-selection(participation~age, frequency~age, ...) Documentation elsewhere describes one method for

Dear R users, I have repeated measurements on individuals. I want to estimate the time-varying effect of a factor variable X (taking three levels), e.g. a model in the spirit of Hastie and Tibshirani (1993). I am considering using the package "mgvc" which implements generalized additive models, especially the function gamm, which estimates generalized additive mixed models, and thus,

Dear R-users, I used lm() to fit a standard linear regression model to a given data set, which led to a coefficient of determination (R^2) of about 0.96. After checking the residuals I realized that they follow an autoregressive process (AR) of order 1 (and therefore contradicting the i.i.d. assumption of the regression model). I then used gls() [library nlme] to fit a linear