similar to: depmixS4 prediction

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

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

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:

I am running a latent class regression with 3 nominal and 2 ordinal variables using depmixS4 but the available response models do not include one for ordinal response.  How do I go about this?   Penny [[alternative HTML version deleted]]

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

Hello, I'm interested in correcting for and measuring unobserved heterogeneity ("missing variables") using R. In particular, I'm searching for a simple way to measure the amount of unobserved heterogeneity remaining in a series of increasingly complex models (adding additional variables to each new model) on the same data. I have a static database of 400,000 or

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

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

Hello. I started using the sem package in R and after a lot of searching and trying things I am still having difficulty. I get the following error message when I use the sem() function: Warning message: In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars, : Could not compute QR decomposition of Hessian. Optimization probably did not converge. I started with a

Hi Can anyone please suggest me a package where I can estimate a non-linear regression model? One of the independent variables is latent or unobserved. I have an indicator variable for this unobserved variable; however the relationship is known to be non-linear also. In terms of equations my problem is y=f(latent, fixed) q=g(latent) where q is the indicator variable For me both f and g are

What should findInterval(x,vec,all.inside=TRUE) return when length(vec)<=1, so there are no inside intervals? R-3.3.0 gives a decreasing map of x->output when length(vec)==1 and -1's when length(vec)==0. Would '0' in all those cases be better? > findInterval(x=c(10, 11, 12), vec=11, all.inside=TRUE, rightmost.closed=FALSE, left.open=FALSE) [1] 1 0 0 >

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

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

In normal tree rotation left process, we will never touch the tree branch above subtree_index and ocfs2_extend_rotate_transaction doesn't reserve the credits for them either. But when we want to delete the rightmost extent block, we have to update the rightmost records for all the rightmost branch(See ocfs2_update_edge_lengths), so we have to allocate extra credits for them. What's more,

Dear list, I have the following problem : I want to model a series of observations of a given hospital activity on various days under various conditions. among my "outcomes" (dependent variables) is the number of patients for which a certain procedure is done. The problem is that, when no relevant patient is hospitalized on said day, there is no observation (for which the "number

I'm interested in the Rsolnp package. For their primary function "solnp", one example is given, and there is a reference to "unit tests". Anyone know where these can be found? Also, Rsolnp is used in a few other packages (e.g., depmixS4), but I cannot seem to find source illustrating its call sequence, and the precise definition of the functions passed. Can anyone help?

Hello, I have initial parameters for HMM model and I want to use depmixS4 package. The parameters are in the form intial_prob_matrix=matrix(c(0.07614213, 0.45177665, 0.47208122), nrow=1, ncol=3, byrow = TRUE) transition_matrix=matrix(c(0.46666667,0.46666667,0.06666667, 0.06741573,0.5617978,0.37078652, 0.02173913,0.3478261,0.63043478), nrow = 3, ncol =