search for: pmatrix

..."Labels") <- rownames(rawdata) } else rawdata.dist <- dist(rawdata, method = method.distance) if (!method.transform == "identity") rawdata <- trans(rawdata, method.transform) hclust.results <- hclust(rawdata.dist, method = method.cluster) pMatrix <- cbind(hclust.results$merge, matrix(data = NA, nrow = nrow(hclust.results$merge), ncol = 1)) simprof.results <- simprof.body(rawdata = rawdata, num.expected = num.expected, num.simulated = num.simulated, method.cluster = method.cluster, method.distance = method.d...

...tensity matrix is equal to zero. For example, the probabilities of moving from 7,8 and 10 to state 11 should be zero. Am I missing something? I hope someone can shed some light on why I am getting 'odd' results? Thanks, Peter -- View this message in context: http://www.nabble.com/msm-and-pmatrix-tp25645397p25645397.html Sent from the R help mailing list archive at Nabble.com.

...(with Rmpi or Rpvm) (as described in http://www.r-project.org/useR-2006/Slides/Harrington+Salibian-Barrera.pd f from the 2006 R User Conference) It is my understanding that this approach is viable, and works with OpenMPI 1.2.4. Is anyone using this method with good results? B. taskpR, RScaLAPACK, pMatrix I read a paper http://sdm.lbl.gov/sdmcenter/projects/SDM.center.parallel.r.2-pager.4.do c coming out of the ORNL, describing what they call "parallel R", which included taskpr, RScaLAPACK, pMatrix. I notice that taskpR is no longer available in "contrib", nor is pMatrix. An ol...

...rt sets various parameters, then there are several functions. The main functions are called bigmatrix and new.bigmatrix which construct the matrices, these should give the same answers, as all I've done is replace the nested loops with outer functions. The Bmatrix calculation is correct but the Pmatrix calculation gets some of the answers wrong. The final lines of code test the functions. Any advice on what's going wrong would be greatly appreciated, also any tips for speeding up the code would fantastic. Many thanks Mark Dr Mark Rees Imperial College, Silwood Park, Ascot, Berks, SL5 7PY...

...ll_model$deviance, reduced_model$df.residual - full_model$df.residual, lower.tail= FALSE); This is not solving my problem meaning my program still stops and gives me the following error: Error in ifelse(y == 0, 1, y/mu) : dim<- : dims [product 9] do not match the length of object [18] Error in pmatrix[perm, ] <- apply(pairs.subset, 1, getLRTp2) : nothing to replace with Can you help me figure out what I have done incorrectly? Thanks for your time, Juliet

Dear all, Currently I am trying to integrate a function which depends on four variables, two of which are given, one is given in the integrate function, so there is one variable to integrate on. The code is as follows: Pmatrix = function(th) { P = matrix(nrow=6, ncol=6, data=0) P[1,1] = P[2,1]=P[3,2]=P[4,3]=P[5,4]=P[6,5]= exp(-th) P[,6] = 1-exp(-th) return(P)} lim.verd = function(matrix) { et = matrix(nrow=1, ncol=dim(matrix)[2], data=1) E = matrix(nrow=dim(matrix)[1], ncol=dim(matrix)[2], data=1) mat =...

...e nnet for my classification problem and have a problem concerning the calculation of the final value for my validation data.(nnet only calculates the final value for the training data). I made my own final value formula (for the training data I get the same value as nnet): # prob-matrix pmatrix <- cat*fittedValues tmp <- rowSums(pmatrix) # -log likelihood finalValue <- sum(-log(tmp)) # add penalty term finalValue + sum(decay * weights^2) where cat is a matrix with cols for each possible category and a row for each data record. The values are 1 fo...

...he response is binary response <- c(rep(1,50),rep(0,50)) # initalize permutation of response 'labels'. perm.response <- response counts <- rep(1,18) # Number of permutations nperm <- 5 # matrix of all pairs of indices all.pairs <- combn2(1:ncol(myData)) # initalize results pmatrix <- matrix(-1,nrow=nperm,ncol=nrow(all.pairs)) getLRTpval <- function(index) { # A contingency table is formed from two columns of the data and the response (3 way table) and made into a vector counts <- as.vector(table(myData[,index[1]],myData[,index[2]], perm.response)); # Add 1...

...* help >>> Building/Updating help pages for package 'mspath' Formats: text html latex example mspath text html latex missing link(s): qmatrix.mspath ematrix.mspath simmulti.mspath print.mspath plot.mspath summary.mspath qmatrix.mspath pmatrix.mspath sojourn.mspath * DONE (mspath) * checking package directory ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking package dependencies ... OK * checking index information ... OK * checking package subdirectories ... OK * checki...

Dear R-experts, this is not a direct R-problem but I hope you can help me anyway. I would like to minimize || PG-I || over P, where P is a p x p permutation matrix (obtained by permuting the rows and/or columns of the identity matrix), G is a given p x p matrix with full rank and I the identity matrix. ||.|| is the frobenius norm. Does anyone know an algorithm to solve such a problem? And if

There is a bug in Matrix package, please check it, thanks! Matlab result: x = 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 >> lu(x) ans = 21.0000 22.0000 23.0000 24.0000 25.0000 0.0476 0.9524 1.9048 2.8571 3.8095 0.7619