similar to: Convert timeseries to transition matrix

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

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

Kia ora I'm a using lme (from nlme package) with data similar to the Orthodont dataset and am getting positive log-likelihoods (>100). This seems usual and I wondered if someone could offer a possible explanation. I can supply a sample dataset if requested, but I feel almost certain that this question has been asked and answered recently. However, I can find no trace of it in the mail

Hi. I'm trying to plot the ratio of used versus unused bird houses (coded 1 or 0) versus a continuous environmental gradient (proportion of urban cover [purban2]) that I would like to convert into bins (0 - 0.25, 0.26 - 0.5, 0.51 - 0.75, 0.76 - 1.0) and I'm not having much luck figuring this out. I ran a logistic regression and purban2 ends up driving the probability of a box being

Hi AlL, I ahve this problem that my objective function is discontinous in the paramaters and I need to use methods such as nelder-mead to get around this. My question is: How do i compute standard errors to a problem that does not have a gradient? Any literature on this is greatly appreciated. Jean,

I am trying to generate kmean of 10 clusters for a 165 x 165 matrix. i do not see any errors known to me. But I get this error on running the script Error: empty cluster: try a better set of initial centers the commands are M <-matrix(scan("R_mutual",n = 165 * 165),165,165,byrow = T) cl <- kmeans(M,centers=10,20) len = dim(M)[1] .... .... I ran the same script last night and

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, 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 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-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

I would like to combine time-series data to test for correlations and interactions using random and fixed effects meta-analysis. So, I am looking for the right packages and documentation. I know about meta and rmeta packages of R. Are there any more? What are the diffrences in brief? Can you please suggest some references that could be used as a guide for meta-analysis in R (or S-plus)?

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

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

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

We are trying to build a human respiration model. Preliminary analysis of some breathing signals has shown that humans breathe through switching among a finite number of patterns. Hidden Markov seems to be the right approach. Since most of our code is written in R scripting language, finding an R package implementing an HMM that we can use for our prototype would be very helpful. I have been

Dear R-users, I haven?t found rules for logical operators. I need to select data according the following rule: Condition A & (Condition B | Condition C) How should I write it?? Is Condition A & Condition B | Condition C correct or will R execute (Condition A & Condition B) | Condition C ? Thanks for your help. Delphine Fontaine Delphine Fontaine Statistician Statistics

Dear All, When installing the Ruuid package (from Bioconductor) from sources on my MAC (OS X 10.3.5, R version 2.0.0) I get the following errors: m00245:~ ivisser$ R CMD INSTALL -l /Users/ivisser/Library/R/library/ /Users/ivisser/Desktop/Ruuid * Installing *source* package 'Ruuid' ... loading cache ./config.cache checking for glib-config... no checking how to run the C preprocessor...

Hello, I tried to fit a poisson distribution but looking at the function fitdistr() it does not optimize lambda but simply estimates the mean of the data and returns it as lambda. I'm a bit confused because I was expecting an optimization of this parameter to gain a good fit... If I would use mle() of stats4 package or mle2() of bbmle package, I would have to write the function by myself