similar to: random roundoff?

Dear R users, I'm using the function coxme of the package coxme in order to build Cox models with complex random effects. Unfortunately, I sometimes get surprising estimations of the variances of the random effects. I ran models with different fixed covariates but always with the same 3 random effects defined by the argument varlist=coxmeMlist(list(mat1,mat2,mat3), rescale = F, pdcheck = F,

Hi, You could try: A<- matrix(unlist(read.table(text=" 1 2 3 4 5 6 7 8 9 9 8 7 6 5 4 3 2 1 ",sep="",header=FALSE)),ncol=3,byrow=FALSE,dimnames=NULL) library(matrixStats) ?res1<-t(sapply(split(as.data.frame(A),as.numeric(gl(nrow(A),2,6))),colProds)) ?res1 #? [,1] [,2] [,3] #1??? 4?? 10?? 18 #2?? 63?? 64?? 63 #3?? 18?? 10??? 4

Is there anyway to change any y[i] value (i=2,...6) to make following NLS workable? x <- c(0,5,10,15,20,25,30) y <- c(1.00000,0.82000,0.68000,0.64000,0.66667,0.68667,0.64000) lm(1/y ~~ x) nls(1/y ~~ a+b*x^c, start=list(a=1.16122,b=0.01565,c=1), trace=TRUE) #0.0920573 : 1.16122 0.01565 1.00000 #Error in numericDeriv(form[[3]], names(ind), env) : # Missing

Dear all, I have run into a problem when running some code implemented in the Bioconductor panp-package (applied to my own expression data), whereby gene expression values of known true negative probesets (x) are interpolated onto present/absent p-values (y) between 0 and 1 using the *approxfun - function*{stats}; when I have used R version 2.8, everything had worked fine, however, after

Dear all, I am using "coxme" function in Kinship library to fit random treatment effect nested within centre. I got 3 treatments (0,1,2) and 3 centres. I used following commands, but got an error. > ugroup=paste(rep(1:3,each=3),rep(0:2,3),sep='/') > mat1=bdsmatrix(rep(c(1,1,1,1,1,1,1,1,1),3),blocksize=rep(3,3),dimnames=list(ugroup,ugroup)) >

Hello together, this is ma first post, so please aplogize me if post this in the wrong section. I have problem concerning ma two matrizes. After a regressione and so on, I got two matrizes Matrixres contains the results of ma calculation. Matrixr contains my detiene, which where Aldo used for the regression. Please ser the following code: #Datei einlesen residual =

Dear all, I am trying to split a matrix into 2 as efficiently as possible. It is a character matrix: 1 2 3 1 "2-271" "2-367" "1-79" 2 "2-282" "2-378" "1-90" 3 "2-281" "2-377" "1-89" I want to make 2 matrices from this, as succinctly and efficiently as possible. I've tried such

HI, I am trying to perform ANOVA with 2 factors: material (3), temperature(3). The interaction is significant. I tried something like, ( summary(avt, split=list("temp:mat"=list("15"=1, "70"=2, "125"=3))) is not correct). Thanks, av <- aov(time ~ mat*temp, data=dados) avt <- aov(time ~ temp/mat) summary(avt,

I have several rasters that I want to do some calculations ,basically calculating the moving average. dir2 <- list.files("D:\\2010+2011", "*.bin", full.names = TRUE) saf=stack(dir2) movi <- overlay(stack(saf),fun=function(x) movingFun(x, fun=mean, n=3, na.rm=TRUE)) Error in .overlayList(x, fun = fun, filename = filename,

How can I control de "wrap-around" color behaviour in the persp function ? I am using something like : persp(bb[1:100,2:97], col= rainbow(8,start=0.1, end=0.8))) Depending on the rainbow length value I get several "wrap-around" blocks of the selected color range...something that I wanted to avoid... My idea is to use the color in order to make a separation from a certain

HI, May be this helps: set.seed(24) ?mat1<- matrix(sample(1:60,30*24,replace=TRUE),ncol=24) colnames(mat1)<- rep(c("O","H","L","C"),6) indx<-seq_along(colnames(mat1)) n<- length(unique(colnames(mat1))) ?res<- lapply(split(indx,(indx-1)%%n+1),function(i) mat1[,i]) lapply(res,head,2) #$`1` #????? O? O? O? O? O? O #[1,] 18 56 51 24 24 52 #[2,]

Dear List, I want to compare the presence and absence of bird species based on the sites in a matrix. The matrix has 5 rows for Island A, B, C, D, and E. It has 100 columns for bird species D001-D100. In each cell of the matrix, the presence-absence of bird species will be recorded as 1 or 0. (For example, if species D001 is found on Island D, the matrix cell of species D001 and Island D

I have generated the following: x= E1 E2 E3 D1 0 0 1 D2 1 0 3 D3 0 2 0 y= E1 E2 E3 D1 0 0 1.75 D2 1.75 0 1.3125 D3 0 3.5 0 Where x and y are linked by: y =sum(x) * x / (rowSums(x)%o%colSums(x)) N=x[x[1:3,]>0] R=y[y[1:3,]>0] Now suppose I

Thanks everyone for the replies. After some experimentation, I found that the order in which the passes are specified matters: opt -O3 -profile-loader matmult.bc -o matmult.opt.bc (works) opt -profile-loader -O3 matmult.bc -o matmult.opt.bc (does not work) Also, I am able to avoid the inconsistency warning only for optimization levels -O3 and -O2. I get that warning when using -O1 and

Hi, I was trying to make a 3D plot using densCols. The documentation for densCols doesn't look like it'll work for 3D. For example: ----------------------------------------- library(scatterplot3d) v1 <- rnorm(10000) v2 <- rnorm(10000) v3 <- rnorm(10000) ## 2D with denscols mat1 <- cbind(v1,v2) mcols1 <- densCols(mat1) plot(mat1,col=mcols1) mat <- cbind(v1,v2,v3)

R-3.0.1 rev 62743, binary downloaded from CRAN just now; macosx 10.8.3 Hello, eigen(symmetric=TRUE) behaves strangely when given complex matrices. The following two lines define 'A', a 100x100 (real) symmetric matrix which theoretical considerations [Bochner's theorem] show to be positive definite: jj <- matrix(0,100,100) A <- exp(-0.1*(row(jj)-col(jj))^2) A's being

On Saturday 31 January 2009 03:42:04 Eli Friedman wrote: > On Fri, Jan 30, 2009 at 5:43 PM, Jon Harrop <jon at ffconsultancy.com> wrote: > > I just remembered an anomalous result that I stumbled upon whilst > > tweaking the command-line options to llvm-gcc. Specifically, the -msse3 > > flag > > The -msse3 flag? Does the -msse2 flag have a similar effect? Yes: $

I just remembered an anomalous result that I stumbled upon whilst tweaking the command-line options to llvm-gcc. Specifically, the -msse3 flag does a great job improving the performance of floating point intensive code on the SciMark2 benchmark but it also degrades the performance of the int-intensive Monte Carlo part of the test: $ llvm-gcc -Wall -lm -O3 *.c -o scimark2 $ ./scimark2

Hi, Not sure if this is what you wanted: ?mat1<- as.matrix(read.table(text=" ????? 33??????? 45??? 50 ????? NA?????? NA?? 54 ",sep="",header=FALSE)) mat2<- as.matrix(read.table(text=" 24??????????????? 0.0000000??????? 0.0000000 0.0000000??????? 14??????????????? 0.0000000 0.0000000 0.0000000??????? 10 ",sep="",header=FALSE)) ?mat1%*%mat2 ?# ??? V1?

Dear useRs, i am using NbClust to determine appropriate number of cluster for hclustering. i am consistently getting the following error Error in if (is.na(n) || n > 65536L) stop("size cannot be NA nor exceed 65536") : missing value where TRUE/FALSE needed Does any one know where i am wrong?? thanks in advance eliza [[alternative HTML version deleted]]