similar to: information matrix in random effects model

Hi All, Does someone have an idea of how to cleverly convert a categorical timeseries into a transition matrix? Ie, I have something like: x<- c(1,1,2,1,1,2,2,2,1,2), And I want a matrix with counts and/or probabilities: > tr <- matrix(c(2,3,2,2),2,2) > tr [,1] [,2] [1,] 2 2 [2,] 3 2 Meaning that there are two transitions from 1 to 1, two from 1 to 2, three from 2 to 1

Is there a package in R that handles general linear (in-)equality + box constrained optimization? If it is not there, could anyone advise me which way to go? And/or point me to packages that solve these problems partially? best, ingmar -- Ingmar Visser Department of Psychology, University of Amsterdam Roetersstraat 15, 1018 WB Amsterdam The Netherlands http://users.fmg.uva.nl/ivisser/ tel:

Hi all, I'm writing a vignette for my package, and I would like to include some of the package help files in there as well. Is there an easy way of doing so? I tried using R CMD Rdconv to generate latex files from .Rd files but I am not sure how to include these into a .Rnw file (ie the vignette source). The resulting file from Rdconv do not readily compile using latex ... The other option I

I had written a vignette and included a \usepackage{Rd} command to make it possible to include latex'ed Rd files in the vignette. However, when loading Rd.sty texShop produces the following error: l. 180 ...d}[1]{\ifmmode\bm{#1}\else\textbf{#1}\fi} This is on Max OS X 3.9 and R 2.0.1 Has anyone seen this before and/or is it problematic? I'm not sure whether the output suffers from this

Dear R-helpers & Friedrich Leisch, I'm trying to fit a mixture of regression models on attached data set by doing the following: agl <- read.table("agl.txt") mod1 <- flexmix(resp~gng+csc|Subject,data=agl, model=FLXglm(family="binomial"),k=2) The result is a (varying) number of the following warnings: Warning messages: 1: non-integer #successes in a

Dear R-help, I'm facing a problem with defining a repeated measures anova with weighted data. Here's the code to reproduce the problem: # generate some data seed=11 rtrep <- data.frame(rt=rnorm(100),ti=rep(1:5,20),subj=gl (20,5,100),we=runif(100)) # model with within factor for subjects/repeated measurements, no problem aov(rt~ti + Error(subj/ti),data=rtrep) #model with weights

Dear R-help, I'm trying to load the fGarch package and keep running into problems with tcltk: After succesfully instaling fGarch (and dependencies) I get: >library(fGarch) Loading required package: fBasics Loading required package: fImport Loading required package: fSeries Loading required package: robustbase Loading required package: fCalendar Loading required package: MASS Loading

Hi, When running R CMD check I'm getting a number of errors that I don't quite follow and don't know where to start looking for an answer, any hints appreciated. R CMD check trunk * checking for working latex ... OK * using log directory '/Users/ivisser/Documents/projects/ depmixProject/depmixNew/rforge/depmix/trunk.Rcheck' * using R version 2.6.2 (2008-02-08) * checking

Hi All, I'm building a package using C/C++ and Fortran code which usually runs fine. However I do get occasional bus errors around the time of exiting one of the C functions. Where do I need to be looking to solve this problem? Do bus errors stem from unmapped memory exceptions? How can I find out if that is what is happening while running R? Any hints greatly appreciated. Best, ingmar

On Tue, 30 May 2023 17:43:31 +0000 Heather Lucas <hlucas2 at lsu.edu> wrote: > Hello, > > I've been enjoying using the "Mixture and Hidden Markov Models in R" > by Visser & Speekenbrink to learn how to apply these analyses to my > own data using depmixS4. > > I currently have a fitted 4-state mixture model with three emissions > variables and one

Hi All, a colleague wants to calculate the Fisher information matrix for a model he wrote (not in R). He can easily get the neg-log-likelihood and the best fit parameters at the minimum. He can also get negLLs for other parameter values too. Given these data, is there a way in R to calculate the Fisher information matrix? Best, Federico -- Federico C. F. Calboli Department of Epidemiology

Dear useRs, I'm trying to create a barplot like so: x=matrix(1:10,2,5) barplot(x,leg=c("left","right"),besid=T) The legend is placed in default position topright, however the data are plotted there too. I tried controlling the legend position by adding x="topleft" but this results in an error that x matches multiple formal arguments. Leaving out the legend

Hi All, I was updating my help pages for a package when all of a sudden I got the following error when using R CMD INSTALL: >>> Building/Updating help pages for package 'depmix' Formats: text html latex example Error in load(zfile, envir = envir) : error reading from connection Removing all the help files makes the error disappear, but only removing the help file that I

Hi all, I am working on Macos x 10.3 (Panther) to build a package consisting of C/C++ code that is called from R. In the C/C++-sources I use several commands to print info to the console: std::cout << "info" << endl; and: Rprintf("info\n"); Both work fine when R is run on the command line but neither works when running Raqau (I did check the preference boxes

Hello All, In some package I use a c-routine which calls a fortran routine which expects a char-string as input. As per the writing R-extensions manual, the Fortran routine is declared in C as: void F77_NAME (setoptions) (char **option); and then it is calles as follows: char **option; option = new char*[1]; option[0] = new char[256]; option[0] = strcpy(option[0],"Iteration

Dear R-Help List, I'm trying to implement Firth's (1993) bias correction for log-linear models. Firth (1993) states that such a correction can be implemented by supplementing the data with a function of h_i, the diagonals from the hat matrix, but doesn't provide further details. I can see that for a saturated log-linear model, h_i=1 for all i, hence one just adds 1/2 to each count,

Dear R community, I am looking for an R package or other software to study hidden Markov models. I need to be able to incorporate multivariate emissions and covariates for the transition probabilities. The msm package seems almost perfect for my purpose, but I do not think it allows multivariate emissions. I will be grateful for your suggestions. All the best, -- Emilio A. Laca One

-- R Help List -- I am looking for a bivariate normal cdf routine in R. I have some fortran routines for this, which appear to be based on 15-point quadrature. Any guidance/suggestions on making these in loadable R-functions would be appreciated. Thanks, Dan =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= Daniel A. Powers, Ph.D. Department of Sociology University of Texas at Austin

gamlss.mx can fit these I believe (although no experience with these myself) flexmix may be (relatively easily) adaptable to accomplish this as well hth, Ingmar Ingmar Visser Universitair Hoofddocent ontwikkelingspsychologie | Directeur College Psychologie Afdeling Psychologie | Faculteit Maatschappij- en Gedragswetenschappen | Universiteit van Amsterdam Bezoek | Nieuwe Achtergracht 129B | Kamer

Dear all, does anyone have r code to perform model-averaging of regression parameters by Akaike weights, and/or to do all-possible-subsets lm modelling that reports parameter estimates, AICc and number of parameters for each model? I have been looking for these in the archive but found none. (I am aware that many of you would warn me against these methods advocated by Burnham and Anderson