similar to: Printing labeled summary to text file ?

Dear List, I thought it would be much easier to put a second query into a second mail. I need to print 426*10000 blocks of variance components data, where 426 is the number of columns of data that have 10000 permutations of variance generated for each of them. I have tried printing out a smaller number of permutations for a smaller number of markers and that has worked. However, since a

Dear all, Does anyone have any suggestions on how to block multiple columns of data one at a time in the midst of an analysis, having specified the blocking variable? I am running a random effects model using lmer, and my data set has multiple columns. Individuals in the study are grouped into 60 families- which is the blocking factor. The random effects are markers (labeled Pxlyy below)

---------- Forwarded Message ---------- Date: 18 September 2009 19:24 +0100 From: A Singh <bzwas at bristol.ac.uk> To: William Dunlap <wdunlap at tibco.com> Subject: RE: [R] Error: length(f1) == length(f2) is not TRUE Yup, they are all factors- and its still doesn't work. Getting to the stage where I can use 'summary()' is the problem- the error stalls the process before a

Dear R users, I am trying to fit an lmer model with only random effects which is giving me the following error: Error : length(f1) == length(f2) is not TRUE In addition: Warning messages: 1: In P1L55:family : numerical expression has 390 elements: only the first used 2: In P1L55:family : numerical expression has 390 elements: only the first used I am trying to extract variance components

Dear All, I am quite new to R and am having a problem trying to run a linear model with random effects/ a regression- with particular regard to my variable lengths being different and the models refusing to compute any further. The codes I have been using are as follows: vc<-read.table("P:\\R\\Testvcomp10.txt",header=T) >> attach(vc) > > family<-factor(family) >

Dear Mark and the R list, I apologise greatly for not having thanked you earlier for your help with my last mail, which involved trying to sort out variance components using two methods: a direct looped lmer, and a two-step analysis involving regressions of AFLP markers on lmer residuals for the same result (or so I hoped). I was in India for ten days and no CRAN mirror in the vicinity made

Dear List, I'm having a curious problem with lapply(). I've used it before to convert a subset of columns in my dataframe, to factors, and its worked. But now, on re-running the identical code as before it just doesn't convert the columns into factors at all. As far as I can see I've done nothing different, and its strange that it shouldn't do the action. Has anybody

Dear alltogether, two lme's, the data are available at: http://www.anicca-vijja.de/lg/hlm3_nachw.Rdata explanations of the data: nachw = post hox knowledge tests over 6 measure time points (= equally spaced) zeitn = time points (n = 6) subgr = small learning groups (n = 28) gru = 4 different groups = treatment factor levels: time (=zeitn) (n=6) within subject (n=4) within smallgroups

fit1<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc) fit2<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.5,data=wbc) fit3<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc) fit4<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc)

Dear List, After including cluster() option the coxreg (from eha package) produces results slightly different than that of coxph (from survival) in the following time-dependent treatment effect calculation (example is used just to make the point). Will appreciate any explaination / comment. cheers, Ehsan ############################ require(survival) require(eha) data(heart) # create weights

I'm trying to figure out how to carry out a Poisson regression fit to longitudinal data with a gamma distribution with unknown shape and scale parameters. I've tried the 'lmer4' package's glmer() function, which fits the Poisson regression using: library('lme4') fit5<- glmer(seizures ~ time + progabide + timeXprog + offset(lnPeriod) + (1|id), data=pdata,

Hi, ? I'm trying to carry out Cramer von Mises tests between pairs of vectors belonging to a discrete distribution (concretely frequencies from 0 to 200). However, the program crashes in the attempt. The problem seems to be that these vectors only have positive integer numbers (+ zero). When I add a random very small positive decimal to the non-decimal part everything works fine (files prm1

Dear group, Here is my df : df <- structure(list(DESCRIPTION = c("PRM HGH GD ALUMINIUM USD 09/07/10 ", "PRM HGH GD ALUMINIUM USD 09/07/10 ", "PRIMARY NICKEL USD 04/06/10 " ), CREATED.DATE = structure(c(18361, 18361, 18325), class = "Date"), QUANITY = c(-1L, 1L, 1L), CLOSING.PRICE = c("2,415.90", "2,415.90",

Dear group, Here is my data.frame : df <- structure(list(DESCRIPTION = c("PRM HGH GD ALU", "PRM HGH GD ALU", "PRIMARY NICKEL", "PRIMARY NICKEL", "PRIMARY NICKEL", "PRIMARY NICKEL", "STANDARD LEAD ", "STANDARD LEAD ", "STANDARD LEAD ", "STANDARD LEAD ", "STANDARD LEAD ",

Dear List, I need to print out each of 'k' levels of a factor 'n' times each, where 'n' is the number of elements belonging to each factor. I know that this can normally be done using the gl() command, but in my case, each level 'k' has an unequal number of elements. Example with code is as below: vc<-read.table("P:\\Transit\\CORRECT

I've been trying with no success to model mixtures of Gamma distributions using the package flexmix (see examples below). Can anyone help me get it to model better? Thanks very much. -Ben ## ## Please help me get flexmix to correctly model mixtures of ## Gamma distributions. See examples below. ## library('flexmix') ## ## Plot a histogram of dat and the Gamma mixture model given

Dear R users, I am trying to read in a file with 105 columns, and when trying to attach it, get an error as follows: > vc1<-read.table("P:\\R\\Everything-I.txt", header=T, sep=" ", dec=".", na.strings=NA, strip.white=T) > attach(vc1) Error in attach(vc1) : variable names are limited to 256 bytes Is there a way to get around this, and make R accept the

I am still having some difficulties with connecting R to a C++ function. I am able to call the function as expected after compiling the shared library and such. However, the call to the function is via .C; parameters from the .C call are not being passed correctly to the function. As an example, I have attached a GDB run of the code. I set a breakpoint on entry to the function I am calling

Found this solution. It is maybe not the most elegant way, but it does the job. > a=as.data.frame(substr(lme$DESCRIPTION,1,14)) > colnames(a)=c("DESCRIPTION") > lme=as.data.frame(c(a,lme[,2:3])) > lme DESCRIPTION CLOSING.PRICE POSITION 1 PRIMARY NICKEL 25,755.7100 0 2 PRIMARY NICKEL 25,760.8600 0 3 PRM HGH GD ALU 2,415.9000 0

I HAVE A VERY BIG DATA OF 67 COLMS AND 25000 ROWS AND WOULD LIKE TO TRANSPOSE IT THE R HELP WAS NOT ENOUGH INFORMATION BECOUSE I AM NOT A PROGRAMMER AND FIRST TIME R USER. SO CAN YOU GIVE SOME HINTS OF CODING, AA TT GG GG CC AA TT GG GG CC AA TT GG GG CC AA TT GG GG CC AA TT GG GG CC TO AA AA AA AA AA TT TT TT TT TT GG GG GG GG GG GG GG GG GG GG CC CC CC CC CC [[alternative HTML