similar to: Error message in Design library

Hello, I'm trying to import a SAS file made using SAS on Unix. Currently I'm using SAS on Windows and I'm trying to import that .ssd04 file to R. The file name of the file is testfile.ssd04 and it is located in 'M:\sasuser'. I'm using Windows XP and R 2.91. Basically what I'm doing is ############ r code ############## > library(foreign) > sashome <-

I have a dataset that I'm trying to rearrange for a repeated measures analysis: It looks like: patient basefev1 fev11h fev12h fev13h fev14h fev15h fev16h fev17h fev18h drug 201 2.46 2.68 2.76 2.50 2.30 2.14 2.40 2.33 2.20 a 202 3.50 3.95 3.65 2.93 2.53 3.04 3.37 3.14 2.62 a 203 1.96 2.28 2.34 2.29 2.43 2.06 2.18 2.28 2.29 a

Hi folks, I'm trying to consolidate the outputs (of anova() and lrm()) from multiple runs of single-variable logistic regression. Here's how the output looks: ------------------------------------------------------------ y ~ x1 y ~ x2 y ~ x3 y ~ x4 Chi-Square 0.1342152 1.573538 1.267291 1.518200 d.f. 2 2

Hi, I have two questions regarding the cloud function in the lattice package: 1) Is there a way to not print the surrounding frame (i.e. the square surrounding the entire plot)? 2) Is there a way to italicize the text displayed with the key argument? Some sample code: data(iris) cloud(Sepal.Length~Petal.Length*Petal.Width,data=iris, groups=Species,screen=list(z=20,x=-70),

Hi there, Could anyone please help me to understand what should be done in order not to get this error message: Error: evaluation nested too deeply: infinite recursion / options(expressions=)? Here is my code: determinant<- function(x){det(matrix(c(1.0,0.2,0.5,0.8,0.2,1.0,0.5,0.6,0.5,0.5,0.5,1.0,x,0.8,0.6,x,1.0),ncol=4,byrow=T))} matrix<-

I have written a wrapper for heatmap.2 called heatmap.w.row.and.col.clust which auto-generates breaks using breaks<-round((c(seq(from=(-20 * stddev), to=(20 * stddev))))/20, digits = 2) #(stddev in this case = 2.5) This has always worked well in the past but now I am getting an error that non-finite breaks are being generated. Drilling down, it seems that my wrapper is generating finite

Dear all, I know there have been various questions posted over the years about loops but I'm afraid that I'm still stuck. I am using Windows XP and R 2.9.2. I am generating some data using the multivariate normal distribution (within the 'mnormt' package). [The numerical values of sanad and covmat are not important.] > datamat <-

Hi, I'm running into an error message for the "anova"-function I never got before with the Design (Version 2.2-0) package. There seems to be a missing function "Varcov", please check my function calls (it's in german but I think you get the error): > library(Design) ## attaching Design package and dependent packages Lade n?tiges Paket: Hmisc ## loading

What is 1. par.ests <- optimfit$par 2. fisher <- hessb(negloglik, par.ests, maxvalue=maxima); 3. varcov <- solve(fisher); 4. par.ses <- sqrt(diag(varcov)); Thanks a lot, fit.GEV <- function(maxima) { sigma0 <- sqrt((6. * var(maxima))/pi) mu0 <- mean(maxima) - 0.57722 * sigma0 xi0 <- 0.1 theta <- c(xi0, mu0, sigma0) #10/5/2007: removed assign() for maxima.nl

Hi, I'm trying to get data from web page and modify it in R. I have a problem with encoding. I'm not able to get encoding right in htmlTreeParse command. See below > library(RCurl) > library(XML) > > site <- getURL("http://www.aarresaari.net/jobboard/jobs.html") > txt <- readLines(tc <- textConnection(site)); close(tc) > txt <- htmlTreeParse(txt,

I have always avoided missing data by keeping my distance from the real world. But I have a student who is doing a study of real patients. We're trying to test regression models using multiple imputation. We did the following (roughly): f <- aregImpute(~ [list of 32 variables, separated by + signs], n.impute=20, defaultLinear=T, data=t1) # I read that 20 is better than the default of

After upgrading R to 2.9.2, I can't use the anova() fuction. It says "could not find function "Varcov" ". What's wrong with my computer? Help needed, thanks! Yao Zhu Department of Urology Fudan University Shanghai Cancer Center No. 270 Dongan Road, Shanghai, China [[alternative HTML version deleted]]

Hi,I am using the amazing package 'plyr". I have one problem. I would appreciate help to fix the following error: Thanks. ______________________________ > library(plyr) > data(baseball) > summarise(baseball, + duration = max(year) - min(year), + nteams = length(unique(team))) Error: could not find function "summarise" > ddply(baseball, "id", summarise, +

I installed the (binary) biOps package, which can use libtiff and libfftw. Then I used macports to install the libraries (in /opt/local/lib). But I restart R and biOps still does not see the libraries. I've tried adding symbolic links from /opt/local/lib to /usr/local/lib, I've added /opt/local/lib to LIBRARY_PATH, LD_LIBRARY_PATH, and DYLD_LIBRARY_PATH, and it doesn't work. Do you

Hello, has anybody written a function to plot density ellipses (95%, 99% or anything) in a scatterplot? I found nothing in any package, nor in the list archives. There does seem to be a contributed package "ellipse" for S-Plus (on S-Archive), but it does a lot more than what I would need. Still, if anybody ported it to R, I'd be grateful for a link. I'm a bit afraid to try the

Dear R-list member, I'm using the function pmnorm() (-->library(mnormt)) within a for-loop. Certain parameter values leads to an error message: "(In sqrt(diag(S)) : NaNs produced, In sqrt(1/diag(V)) : NaNs produced, In cov2cor(S) : diag(.) had 0 or NA entries; non-finite result is doubtful)" obviously because "NaNs" were produced. Is it possible to tell R that it

Can anyone tell me what I might be doing incorrectly for an ordinal logistic regression for lrm? I cannot get R(2.9.1)to run either summary nor will it let me bootstrp to validate. ### Y is a 5 value measure with a range from 1-5, the independent variables are the same. N=75 but when we knock out the NAs it comes down to 51#### > lrm(formula = Y ~ permemp + rev + gconec + scorpstat, data =

Dear List: I am estimating a gls model and am having to make some rather unconventional modifications to handle a particular problem I have identified. My aim is to fit a GLS with an AR1 structure, obtain the variance-covariance matrix (V), modify it as needed given my research problem, and then reestimate the GLS by brute force using matrix operations. All seems to be working almost perfectly,

Hi All. I'd like to generate a sample of n observations from a k dimensional multivariate normal distribution with a random correlation matrix. My solution: The lower (or upper) triangle of the correlation matrix has n.tri=(d/2)(d+1)-d entries. Take a uniform sample of n.tri possible correlations (runi(n.tr,-.99,.99) Populate a triangle of the matrix with the sampled correlations Mirror the

I found a strange inconsistency: If m is a matrix and d is a data frame then - mean(m), median(m), max(m) and max(d) all return a single value but - mean(d) returns the column means - median(d) fails - both var(m) and var(d) return the variance covariance matrix You pretty much have to experiment to figure this out since much of this behavior is not readily obvious from the help files.