similar to: var-covar matrices comparison

Hi, Using package gclus in R, I have created some graphs that show the trends within subgroups of data and correlations among 9 variables (v1-v9). Being interested for more details on these data I have produced also the var-covar matrices. Question: From a pair of two subsets of data (with 9 variables each, I have two var-covar matrices for each subgroup, that differ for a treatment on one

Hi there, If I do an lm, I get p-vlues as p-value: < 2.2e-16 Suppose am interested in exact value such as p-value = 1.6e-16 (note = and not <) How do I go about it? stephen

I don't know of any R package that can match all the functionality of LEM eg fitting equality constraints to model parameters a la LISREL. WRT dumping tables, I would have thought that as.data.frame.table does pretty much what you want, [not tested] newtab <- as.data.frame(table(a,b,c)) cat("dim\n") for(i in seq(1, ncol(newtab)-1) { cat(nlevels(newtab[,1]," ") }

Hi. I just noticed the paper by Morales and Nocedal Remark on "Algorithm 778: L-BFGS-B: Fortran Subroutines for Large-Scale Bound Constrained Optimization". TOMS 2011; 38(1): 7 http://www.ece.northwestern.edu/~morales/PSfiles/acm-remark.pdf which describes a couple of improvements (speed and accuracy) to the original Netlib code which AFAICT is that still used by optim() via f2c.

Newsgroup members, I appreciate the help on this topic. David Duffy provided a solution (below) that was quite helpful, and came close to what I needed. It did a great job creating two vectors of dichotomous variables with a known correlation (what I referred to as a phi-coefficient). My situation is a bit more complicated and I'm not sure it is easily solved. The problem is that I must

A bit late, but you might like to look at http://www.qimr.edu.au/davidD/polyr.R Regarding the original posters queries: You can analyse polychoric correlations as if they were Pearson correlations using standard software (eg sem), and this usually doesn't do too badly, or go to AWLS (Browne) in LISREL etc, or ML analysis of the full multidimensional contingency table using programs such as

I couldn't resist adding a more literal answer unback <- function(x) { chars <- unlist(strsplit(deparse(x),"")) chars <- chars[-c(1,length(chars))] paste(gsub("\\\\","/",chars),collapse="") } unback("\n") | David Duffy (MBBS PhD) ,-_|\ | email: davidD at qimr.edu.au ph:

I couldn't resist adding a more literal answer unback <- function(x) { chars <- unlist(strsplit(deparse(x),"")) chars <- chars[-c(1,length(chars))] paste(gsub("\\\\","/",chars),collapse="") } unback("\n") | David Duffy (MBBS PhD) ,-_|\ | email: davidD at qimr.edu.au ph:

If I run an analysis which generates statistical tests on many SNPs I would naturally want to get more details on the most significant SNPs. Directly from within R one can get the information by loading RSNPer (from Bioconductor) and simply issuing a command SNPinfo(2073285). Unfortunately, the command cannot handle a vector and therefore only wants to do one at a time. I tried the lapply and

Hi. I don't know if this a bug or just annoying to me: > x <- c(1,2,3,NA) > table(x, exclude=NULL) x 1 2 3 <NA> 1 1 1 1 > table(factor(x), exclude=NULL) 1 2 3 1 1 1 I don't think many people use factor(x, exclude=NULL): it is not the default handling of character data by read.table(). Cheers, David Duffy. -- | David Duffy (MBBS PhD)

Hi, Is there a smart way in the R graphs to create a line that is broken in intervals based on the indicator given below. following is a small test graph Location,indicator,otherinfo 1.2,1,2.2 2.5,1,2.5 3.7,1,2.3 20.1,2,4.3 22.5,2,5.2 25.0,2,3.4 27.3,2,2.2 35.1,3,3.4 37.0,3,7.2 38.0,3,6.1 40.1,3,5.4 52.9,3,3.3 Right now in the plot the line is continuous, but I would like to have it broken

Hi, If I use x<-1:10 y<-rnorm(10,0,1) ### pdf(file="c:\\aldi\\test.pdf") plot(x,y) segments(x,y,x+2,y+2) segments(x,y,x+0.5,y+0.5,col=3) ### dev.off() ### q() Is there a way that I can imbed in the graph plot for each point defined by x to x+0.5 and y to y+0.5 (and colored in green) a different hyperlink? For example point one (together with the green tail) will have the

Hi, I am looking to do some quantitative genetic analyses using animal models and was wondering if someone could suggest an appropriate package in R. It would help if it was similar to the ASReml genetic analyses software. Thanks, Deepa Senapathi Deepa Senapathi Centre for Agri-Environmental Research (CAER) School of Agriculture, Policy & Developement. University of Reading

Does anyone know if the sib TDT has been implemented in R 1. Spielman, R.S., and Ewens, W.J. (1998) A sibship test for linkage in the presence of association: the sib transmission/disequilibrium test. Am J Hum Genet 62, 450-458 -- Farrel Buchinsky, MD Pediatric Otolaryngologist Allegheny General Hospital Pittsburgh, PA

Hi I was wondering whether anyone can provide any help or suggestions on the boostrap method for latent class analysis please. My main question is: can the bootstrap procedure sometimes be less precise than the non-bootstrap procedure when carrying out latent class analysis? I am asking this question because I carried out some analyses and when I *did not* use the bootstrap procedure I found

Hi, I am trying to install the genetics package on a server with Linux, Fedora. I installed it in a PC and worked fine. In a server since I am not used with R, I am not sure what do I need to change so genetics pkg can see some package dependencies: Any suggestion is appreciated, Aldi Note: genetics expects gregmisc and mvtnorm to be installed already. gregmisc creates gdata etc dependencies.

Dear all, I'm using the package "Genetics", and I'm interested in the computation of D' statistics for Linkage Disequilibrium, for which the LD() command has been realised. Unfortunately I don't find any reference on "how" the D' is computed by the LD() function. In the package documentation it is generally referred as "MLE" estimation, but

Hi, I have a data.frame with many variables for which I am performing the mean by subgroup, for a pair of variables at a time, where one of them for each pair defines the subgroup. The subgroups in the x$cm1 are 0, 1 and 2. x ph1 cm1 0.2345 2 1.2222 1 2.0033 0 0.0000 2 1.0033 1 0.2345 0 1.2222 2 2.0033 0 0.0000 1 1.0033 2 > meanbygroup <- as.vector(with(x, by(x$ph1, x$cm1, mean)))

Hello All R Users, Function loglm() in library MASS can be cajoled to accomodate structural zeros in a cross-classification table. An example from Fienberg demonstrates how this can be done. My question is: Can the function glm() perform the same task? Can glm() estimate a log-linear model with fixed zeros like loglm()? Thanks for your help, Andrew ## Fienberg, The Analysis of Cross-Classified

Dear Colleagues, I am looking for a package or previous implemented R to subgroup and exaustively divide a vector of squence into 2 groups. For example: 1, 2, 3, 4 I want to have a group of 1, (2,3,4) (1,2), (3,4) (1,3), (2,4) (1,4), (2,3) (1,2,3), 4 (2,3), (1,4) ... Can someone help me as how to implement this? I get some imaginary problem when the sequence becomes large. Thanks much in