similar to: low-variance warning in lmer

The sapply function is refusing to return a result for what seem to me to be mysterious reasons. Here is a toy example: set.seed(111) X <- list(x=runif(20),y=runif(20)) rvec <- seq(0.01,0.15,length=42) foo <- function(x,X,cc) { mean((X$x)^x + (X$y)^cc) } bar <- function(x,a,b){a+b*x} try.b <- sapply(rvec,bar,a=1,b=2) # This runs without a problem and

This message contains a description of what looks like a bug, examples of the suspect behavior, a proposed change to the C code to change this behavior, example of behavior with the fix, and suggestions for 3 places to update the documentation to reflect the proposed behavior. It is submitted for consideration for inclusion in R. Comments are requested. Currently, the code for subscripting

I've put this in (with some different wording). Although S blithely accepts mis-dimensioned index matrices I agree this is wrong and have made it an error. On Fri, 29 Apr 2005 tplate@acm.org wrote: > This message contains a description of what looks like a bug, examples > of the suspect behavior, a proposed change to the C code to change this > behavior, example of behavior with

Hi, I am fairly new to R, and am stuck. I want to write an R function with argument n that returns a vector of length n with n simulated observations from the double exponential distribution with density: ??g(y) = 1/2e^-y ? For the double exponential, I want to generate y~Exp(1) and then take ?y with probability 0.5 ? Does anyone know how I can do this in R? Thanks! Fran [[alternative

Dear all I want to simulate a stochastic jump variance process where N is Bernoulli with intensity lambda0 + lambda1*Vt. lambda0 is constant and lambda1 can be interpreted as a regression coefficient on the current variance level Vt. J is a scaling factor How can I rewrite this avoiding the loop structure which is very time-consuming for long simulations? for (i in 1:N){ ... N <- rbinom(n=1,

Hi, Is there a way to stack bars in a barchart as well as "beside" bars for the same treatment? eg.... I have one barchart like this: bio<-matrix(c(10,23,9,25),nrow=2,byrow=T) ntreat<-c("n0","n96") colnames(bio)<-ntreat barplot(bio,beside=T) now i want a similar barchart but with stacked bars:

In S-Plus, I can obtain polynomial contrasts for an ordered factor with contr.poly(). The function also exists in R, however is limited to factors where the levels are equally spaced. In S-Plus, one can obtain the contrasts for a set of numeric values representing unequally spaced ordered factors. Has anyone implemented this in R? I see that the S-Plus function calls another function (poly.raw())

Dear All I would like to produce interaction boxplots and this seems to work: par(mfrow=c(2,2)) A=sample(rnorm(50,50,10)) B=sample(rnorm(50,100,10)) Test=merge(A,B,by=0)#by=0 where 0 is the row.names TreatA=(gl(2,50,100,labels=c("High","Low"))) TreatB=rep(gl(2,25,50,labels=c("High","Low")),2) Newdata=data.frame(TreatA,TreatB,Test)

Dear List: I am working to understand some differences between the results of the svymean() function in the survey package and from code I have written myself. The results from svymean() also agree with results I get from SAS proc surveymeans, so, this suggests I am misunderstanding something. I am never comfortable with "I did what the software" does mentality, so I am working to

Dear R folk: Perhaps I'm just dense today, but I am having trouble reproducing the principal components plotted and summarized by clusplot. Here is a brief example using the pluton dataset. clusplot reports that the first two principal components explain 99.7% of the variability. But this is not what princomp is reporting. I would greatly appreciate any advice. With best regards, -- Tom

Dear R users; Im working with lme and Id like to have an idea of how can I get CI for the predictions made with the model. Im not a stats guy but, if Im not wrong, the CIs should be different if Im predicting a new data point or a new group. Ive been searching through the web and in help-lists with no luck. I know this topic had been asked before but without replies. Can anyone give an idea of