similar to: Labelling and formatting of graphics

Hello. Sorry I am not sure this question should go to llvm or mesa3d-dev mailing list, so I post it to both. I am writing a llvm backend for a modern graphics processor which has a ISA very similar to that of Direct 3D. I am reading the code in Gallium-3D driver in a mesa3d branch, which converts the shader programs (TGSI tokens) to LLVM IR. For the shader instruction also found in LLVM IR,

Alex wrote: > Hello. > > Sorry I am not sure this question should go to llvm or mesa3d-dev mailing > list, so I post it to both. > > I am writing a llvm backend for a modern graphics processor which has a ISA > very similar to that of Direct 3D. > > I am reading the code in Gallium-3D driver in a mesa3d branch, which > converts the shader programs (TGSI tokens) to

Hi, I'm trying to evaluate a Monte Carlo p-value (using truncgof package) on a left truncated sample. >From an empirical sample I've estimated a generalized pareto distribution parameters (xi, beta, threshold) (I've used fExtremes pkg). I'm in doubt on what of the following command is the most appropriate: Let: x<-sample t<-threshold xt<-x[x>t] xihat<-gpdFit(x,

The solve function in r-patched has been changed so that it applies a tolerance when using Lapack routines to calculate the inverse of a matrix or to solve a system of linear equations. A tolerance has always been used with the Linpack routines but not with the Lapack routines in versions 1.7.x and 1.8.0. (You can use the optional argument tol = 0 to override this check for computational

I want use survfit() and basehaz() inside a function, but it doesn't work. Could you take a look at this problem. Thanks for your help. Following is my codes: library(survival) n <- 50 # total sample size nclust <- 5 # number of clusters clusters <- rep(1:nclust,each=n/nclust) beta0 <- c(1,2) set.seed(13) #generate phmm data set Z <- cbind(Z1=sample(0:1,n,replace=TRUE),