search for: q_i

...lowing code : # generate a (1000 x 10001) matrix, testm # generate statistics matrix 1000 x 4: qnt <- c(0.01, 0.05) cmp_fun <- function(x) { LAST <- length(x) smpls <- x[1:(LAST-1)] real <- x[LAST] ret <- vector(length=length(qnt)*2) for (i in 1:length(qnt)) { q_i <- quantile(smpls, qnt[i]) # the quantile i m_i <- mean(smpls[smpls<q_i ] ) # mean of obs less than q_i ret[i] <- ifelse(real < q_i, 1, 0) ret[length(qnt)+i] <- ifelse(real < q_i, real - m_i, 0) } ret } hcvx <- apply(testm, 1, cmp_fun) The c...

Hello, The question looks like simple. It's probably even stupid. But I spent several hours searching Internet, downloaded tons of papers, where deviance is mentioned and... And haven't found an answer. Well, it is clear for me the using of entropy when I split some node of a classification tree. The sense is clear, because entropy is an old good measure of how uniform is distribution.

...into the title of a plot. My best attempt is the following: myplot <- function(var1, var2) { v=paste(var1,"==1 & ",var2,"==2"); plot(1:10, main=parse(,,v)) } But when I call it with something like myplot("Q[i]", "Delta[j]") I get "&(Q_i=1,Delta_j=2)" as title when I want to get "Q_i=1 & Delta_j=2". Is there any solution within R? (I don't want to use psfrag and Latex to post-process the plot) Why R does not have support for full Latex expressions? (as Matlab f.ex.). IMHO plotmath is not good enough. Thank...

Dear all, I am trying to compare the estimated coefficients of a quantile regression model between two different samples. It is a Wald test, but I cannot find one way to do that in R.The samples are collected conditional on a specific characteristic and I would like to test whether such characteristic indeed affect the estimators. The problem in the test anova.rq is that the response variable

...repeated Cholesky factorization of a spares symmetric matrices, say Q_1, Q_2, ...,Q_n, where the Q's have the same non-zero pattern. I know in this case one does only need to carry out the symbolic factorization _once_ and then follow that up with a numerical factorization for each of the Q_i's (re-using the general symbolic factorization each time). Does anybody know if this is possible using the Matrix package? Thanks, Gardar Johannesson Lawrence Livermore National Laboratory

Hi everyone, I'd like a bit of information about the stereo mode settings in psych_44.h of libvorbis. Specifically, about the adj_stereo structure: typedef struct { int pre[PACKETBLOBS]; int post[PACKETBLOBS]; float kHz[PACKETBLOBS]; float lowpasskHz[PACKETBLOBS]; } adj_stereo; What I am attempting to do is bring lossless stereo coupling down to the lower quality levels in

...while(iter < maxIter && not_converged) { /* make v_ij + (1-mu)*ln(q_ij) */ for (j=0; j<H_c; j++) {...

Hello, I?m with a problem in using nonlinear quantile regression, the function nlrq. I want to do a quantile regression o nonlinear function in the form a*log(x)-b, the coefficients ?a? and ?b? is my objective. I try to use the command: funx <- function(x,a,b){ res <- a*log(x)-b res } Dat.nlrq <- nlrq(y ~ funx(x, a, b), data=Dat, tau=0.25, trace=TRUE) But a can?t solve de problem,

On Thu, 12 Apr 2007, Fernando Magno Quintao Pereira wrote: >> I'm definitely interested in improving coalescing and it sounds like >> this would fall under that work. Do you have references to papers >> that talk about the various algorithms? > > Some suggestions: > > @InProceedings{Budimlic02, > AUTHOR = {Zoran Budimlic and Keith D. Cooper and Timothy