similar to: Ordinal response model in depmixS4

Dear helpers, is there any possible that transition (in depmixS4) is in scale of two variable, e.g transition=~scale(x1,x2)? If it can be, how transition of two variable (covariate time) can be worked in depmixS4-hidden markov model for time series. Many thanks, nglthu -- View this message in context: http://r.789695.n4.nabble.com/depmixS4-transition-tp4572726p4572726.html Sent from the R help

Hi I am trying to use depmixS4 package. Based on the documentation, it seems that depmix allows one to fit an HMM model based on a training data with time-varying co-variates. However, I did not find any routines which can help test the accuracy on the fitted HMM model on out-of-sample data. Can someone confirm if that is indeed the case? Also are there any alternate packages for the same? Thanks

I am getting started with using the depmixS4 package. First, I would like to see I am very impressed with its speed and flexibility. The question I have is regarding predicting on new data. I want to fit the model on some sequences with observed responses, and then make predictions on the right end of the sequences where the responses are not observed. I see no prediction functionality anywhere,

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

As an alternative to Latent GOLD, I'm wondering if anyone knows of and R package that can manage Latent Class Analysis with mixed variable types (continuous, ordinal, and nominal/binary). [[alternative HTML version deleted]]

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 binomial covariate (HS). I am trying to compute confidence intervals using the following code, where fmms4s is the model:

depmixS4 has reached some form of maturity and therefore we have bumped its version number to 1.0-0 which is now on CRAN: http://cran.r-project.org/web/packages/depmixS4/index.html depmixS4 fits hidden (latent) Markov models of multivariate, mixed categorical and continuous data, otherwise known as dependent mixture models. Responses or observations can be modeled using GLMs, and additionally

depmixS4 has reached some form of maturity and therefore we have bumped its version number to 1.0-0 which is now on CRAN: http://cran.r-project.org/web/packages/depmixS4/index.html depmixS4 fits hidden (latent) Markov models of multivariate, mixed categorical and continuous data, otherwise known as dependent mixture models. Responses or observations can be modeled using GLMs, and additionally

Package news (see below for general description of functionality) depmixS4 version 1.3-0 has been released on CRAN. See the NEWS file for an overview of all changes. The most important user-visible changes are: 1) more compact pretty-printing of parameters in print/summary of (dep)mix objects (following lm/glm style of presenting results) 2) some speed improvements in the EM algorithm, most

Package news (see below for general description of functionality) depmixS4 version 1.3-0 has been released on CRAN. See the NEWS file for an overview of all changes. The most important user-visible changes are: 1) more compact pretty-printing of parameters in print/summary of (dep)mix objects (following lm/glm style of presenting results) 2) some speed improvements in the EM algorithm, most

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

R Community - I am attempting to fit a model as described in Hampton, Bossaerts, and O'doherty (J. Neuroscience) 2006. They use a bayesian hidden markov model to model the Reversal Learning data. I have tried using HMM and depmixS4 with no success. My data is a Reversal Learning Task in which there are 3 sets of patterns over 3 blocks. The participant receives incorrect or correct

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

I am doing cluster analysis on 8768 respondents on 5 lifestyle variables and am having difficulty constructing a dissimilarity matrix which I will use for PAM.  I always get an error:  “cannot allocate  vector of size 293.3 Mb” even if I have already increased my memory to its limit of 4000.  I did it on 2GB , 32-bit OS .  I tried ff and filehash and I still get the same error.  Can you please

Thank you for your prompt answer. The breathing signal observations are the amplitude values as a function of time and phase. According to our model the hidden states are the different breathing types. Subjects, whose respiratiion process is regular, are likely to breathe, keeping the same cycle pattern/type, for many consecutive cycles. therefore dwelling in the same hidden state. The more

Hi all, I have a question, is there any R package dealing with latent transition analysis with both categorical and continuous indicators? So far what I found from GOOGLE are only packages dealing with latent class analysis. So what about the longitudinal situation? Any way we could look at the transition from one class to another across time points? Thank you very much. ya [[alternative

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Hello All, Does anyone know of a package that performs constraint-based clusters? Ideally the package could perform "Time-Ordered Clustering", a technique applied in a recent journal article by Runger, Nelson, Harnish (using MS Excel). Quote, "in our specific implementation of constrained clustering, the clustering algorithm remains agglomerative and hierarchical, but observations

I have been asked to analyse some questionnaire data- which is not data I'm that used to dealing with. I'm hoping that I can make use of the nabble expertise (again). The questionnaire has a section which contains a particular issue and then questions which are related to this issue (and potentially to each other): 1) importance of the issue (7 ordinal categories from -3 to +3) 2) impact

Dear R users, Is there any package for Latent Class Analysis (to be used in a clustering application) which supports mixed indicator variables (categorical and continuous)? Alternatively, is there any other clustering algorithm available that supports this type of data? Thanks in advance for your help. Regards, Lars. [[alternative HTML version deleted]]