similar to: error checks

I've finally narrowed down a puzzling problem: here is the short test case. tmt34% R --vanilla R version 2.10.0 (2009-10-26) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 > temp <- matrix(runif(50), ncol=2) > t(temp) %*% temp [,1] [,2] [1,] 7.916016 6.049698 [2,] 6.049698 7.650694 > library(kinship) Loading required package:

Hello, I was hoping someone could answer a question for me that may either be statistical or script related. I don't come from a statistics background, so I am not positive if I am using the correct nomenclature or even the correct procedure. Is it possible to model "random coefficients" in a mixed effects cox-regression using coxme from the Kinship package? For example, using

I have library in development with a function that works when called from the top level, but fails under R CMD check. The paricular line of failure is rsum <- rowSums(kmat>0) where kmat is a dsCMatrix object. I'm currently stumped and looking for some ideas. I've created a stripped down library "ktest" that has only 3 functions: pedigree.R to create a pedigree or

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)) >

I am making the question clear. Please help. > Dear R experts > > I was using kinship package to fit mixed model with kinship matrix. > The package looks like lme4, but I could find a way to extract p-value > out of it. I need to extract is as I need to analyse large number of > variables (> 10000). > > Please help me: > > require(kinship) > > #Generating

I have a data frame containing the Id, Mother, Father and Sex from about 10,000 animals in our colony. I am interested in graphing simple family trees for a given subject or small number of subjects. The basic idea is: start with data frame from entire colony and list of index animals. I need to identify all immediate relatives of these index animals and plot the pedigree for them. We're

I wish to make modifications to the plot.pedigree function in the kinship package. My attempts to contact the maintainer have been unsuccessful, but my question is general, so specifics of the kinship package might not be an issue. My first attempt was to make a new function Plot.pedigree in the .GlobalEnv which mostly achieved what I wanted to. However, I'm sure that's not the tidiest

Hi Im using the kinship package to draw a pedigree. On my data set this works fine but when i add indivudals to the pedigree i keep getting an error i hope someone can help me! This is the code im using: Data<-read.table("Tree.txt", header=T, sep=",") attach(Data) ped<-pedigree(id, dadid, momid, sex, aff) par(xpd=T) plot.pedigree(ped) This is my data looks like

Hello! I am building a package, which includes also one Fortran subroutine, which works fine if I compile it as a shared library and load it into R via dyn.load(). However, when I launch R CMD check it doesn't stop with checking examples. It's just doing and doing ... I pasted the whole output from R CMD check. Does anyone have any suggestions? I'm still using R 2.0.1.

The package coxme depends heavily on bdsmatrix, to the point of needing access to some of its C calls. The kinship package (in progress) uses the R level functions in bdsmatrix, but not the C calls. That is, I don't want to always export the symbols. For testing I can use an explicit dyn.load('somepath/bsdmatrix.so', local=F). How do I incorporate such a dependency in the

I had added a vignette to the coxme package and all worked well locally, but it failed at CRAN.???? The issue is that the vignette involves using coxme for pedigree data, it doesn't work without the kinship2 package, and I hadn't put in the necessary "if (require(...." logic. The question is, how do I make the entire vignette conditional? If the package isn't available,

Hi,I use the 'lmekin' model of the 'kinship' package of R in order to estimate heritability. I want to estimate the confidence interval of the variance coefficient and so I should use a bootstrap simulation. The pedigree file has 1386 subjects so I create a kinship matrix [1386*1386].This is the code of R I use: kfit2 <- lmekin(IT~1+AGE +(1|ID), dati1,

I've been looking at the kinship package which looks as though it might be appropriate for my purposes. What I can't find is any reference to the data that is used in the example code. A dataframe called d10 with column names, upn, dadid, momid, sex and affect is required. One can get an idea of what sort of values should be in most columns from the description in the pedigree function,

Dear R users: I'm new to R and am trying to fit a mixed model Cox regression model with coxme function. I have one two-level factor (treat) and one covariate (covar) and 32 different groups (centers). I'd like to fit a random coefficients model, with treat and covar as fixed factors and a random intercept, random treat effect and random covar slope per center. I haver a couple of

User of the coxme library (mixed effects Cox models) are instructed to use ranef(), fixed(), VarCorr(), etc to retrieve bits out of a fitted model; it purposely uses the same methods as nlme and/or lmer. The current behavior is to "depend" on nlme. If I defined the methods myself in coxme, then someone who had both nlme and coxme loaded will suffer from "last loaded wins",

Hello, I am using the Kinship package to draw a pedigree plot. I am trying to control the spacing between individuals in the pedigree. Currently, it is drawing a pedigree with too little space, so the text is overlapping. I'd like to increase the distance between individuals. According to the documentation, I would expect the following to be relevant:

Dear R-help, I am trying to estimate a Cox model with nested effects, or better h(t,v,w)=v*w*h0(t)*exp(B'x) where h(t,v,w) is the individual hazard function w and v are both frailty terms (gamma or normal distributed) I have 12 clusters and for each one of them I would like to associate a realization of v, while w is a random effect for the whole population. At the population level

I have a case where the easiest way to draw a particular symbol would be to draw something a little bigger, and then use polygon(... , col=0) to erase the extra stuff. Just how to do this best when par('bg') = 'transparent' is, however, eluding me. I've looked through the archives and the book R Graphics without quite seeing the light. Help or pointers to help would be

Hello, All, GWAF 1.2 R.Version() is below. system(lme.batch.imputed( phenfile = 'phenfile.csv', genfile = 'CARe_imputed_release.0.fhsR.gz', pedfile='pedfile.csv', phen='phen1', covar=c('covar1','covar2'), kinmat='imputed_fhs.kinship.RData', outfile='imputed.FHS.IBC.GWAF.LME.output.0.txt' )) Gives the error messages: Error in

Dear useRs: Announcing the release of kinship2, version 1.2.1, to CRAN. kinship2 is a branch from the original kinship package with some key updates for the pedigree and kinship functions, with some additional functions that work with the pedigree object. Highlights: * pedigree and pedigreeList objects implemented with S3 methods print and "[," * pedigree plotting routine