similar to: constructing arbitrary (positive definite) covariance matrix

Dear list, Most high performance computing clusters/grid engines have some restrictions on how long a job can be run in batch mode. The cluster I am using has maximum of 48 hours limit, but my job would take far more than that. I know that it is possible to checkpoint jobs without modifying the code if some specialized software (e.g., BLCR ) is installed on the grid engine. However, I am

I have two specific questions regarding the output of lda function in MASS. #Question1: #========= n: sample size, p: number of variables Some articles in the literature say that LDA is singular for p > n-1. However, my experimentation with lda (default arguments) for two class problems shows collinearity for p > n-2. Does anyone know why this is the case? Does lda (MASS) use a different

Hi, there. I have two questions about the diagnostics in multivarite statistics. 1. Is there any diagnostics tool to check if a multivariate sample is from multivariate normal distribution? If there is one, is there any function doing it in R? 2. Is there any function of testing if two multivariate distribution are same, i.e. the multivariate extension of Kolomogrov-Smirnov test? Thanks for

Hi, I am looking for an R package that would calculate multivarite (mostly 2d and 3d, tensor) cubic interpolating splines, so that I could evaluate these splines (and their derivatives) at many points (unkown at the time of calculating the spline polynomials) repeatedly. To make things concrete, I have an array V with dim(V) = k and gridpoint vectors grid=list(...), length(grid[[i]])==k[i],

Hi all, I have a multiple-linear regression problem. There are 13 columns of data, the whole data matrix is: n x 13, where n is the number of samples. Now I want to regress EACH of the first 12 columns onto the 13th column, with 2-parameter linear model y_i = b0 + b1 * x_i, where i goes from 1 to n, and b0 is the intercept. How do I create a design matrix to do the 12-column regression

Dear listers, First let me appologize if the same mail arrives multiple times. Recently I had some probelms sending my e-mails to the list. I encountered a problem when running glmmPQL procuedure doing multilevel modeling with a dichotomous outcome. Those are the two error messages I usually get: Error in logLik.reStruct(object, conLin) : NA/NaN/Inf in foreign function call (arg 3)

Hi, I've been trying to figure out a special set of covariance matrices that causes some symmetric zero elements in the inverse covariance matrix but am having trouble figuring out if that is possible. Say, for example, matrix a is a 4x4 covariance matrix with equal variance and zero covariance elements, i.e. [,1] [,2] [,3] [,4] [1,] 4 0 0 0 [2,] 0 4

Hi listers, In light with the recent discussion on the optimizing the use of memory in straneous proceudres i present you m problem, and hope to some additional ideas. I'm running a simualtion that in each step uses quite an amount of memory (but not exceedingly) - just to give you an idea - I create a pseudo population (n=1000, m=3) run lme and lm model and multiply impute (M=5) and do the

I find the documention for RNGversion in R-devel is a bit misleading, and suggest adding a sentence to make it clear that the meaning of "default" is not set to its meaning in the earlier R version: `RNGversion' can be used to set the random generators as they were in an earlier R{} version (for reproducibility). RNGversion does not set the meaning of