search for: hmms

Displaying 11 results from an estimated 11 matches for "hmms".

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2008 Nov 11
1
R: R: Hidden Markov Models
...understand. Thank you in advance for your attention. Kind regards, Maura Edelweiss -----Messaggio originale----- Da: Walter Zucchini [mailto:wzucchi@uni-goettingen.de] Inviato: mar 11/11/2008 11.32 A: mauede@alice.it Oggetto: Re: R: Hidden Markov Models Dear Ms Monville, Hidden Markov models (HMMs), and that includes the msm implementation, are not based on the assumption that the observations are independent. Indeed HMMs are specifically designed to model serially dependent observations. Of course that doesn't mean that they can accommodate every type of serial dependence. It might...
2013 Sep 02
1
Multivariate discrete HMMs
...wondering if RHmm can be used to model a multivariate discrete HMM, i.e., the observations are a vector of discrete measurements? From what I see in the documentation and from playing around with examples, it seems like this may not be possible. My understand of the mathematics behind multivariate HMMs is limited, so I would appreciate any advance you might be able to give. Thanks for any help anyone can give
2009 Jul 10
2
drawing hmms
Hi, I need to draw hmm's in R.I also need to include a small plot near each state of the hmm.How can I do this? -- Rajesh.J [[alternative HTML version deleted]]
2011 Dec 19
1
Training parameters for a HMM
Hi, I'm a newbie to the world of HMMs and HMMs in R. I've had a look at the hmm package and the RHmm package but I couldn't see anything straightforward on how a labelled sequential dataset with observed values and underlying states might be used to construct and train a HMM based on that data and no pre-computed values for the...
2008 Nov 09
1
choice of an HMM package
...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 suggested both *msm* and *depmixS4.* I have no previous experience with HMMs and feel at a loss about making a sensible choice. As a novice I am more attracted by msm because of the comprehensive documentation, with worked out examples, that I am printing out. Whereas I could not find anything but the usual R function call description for depmixS4. Moreover, I cannot make a...
2011 Jan 26
0
hmm.discnp hidden markov model
...s for observations and K is the number of hidden states. my_hmm <- hmm(y=signature, yval=c(-110:-6), K=5) print(my_hmm) The above shows that the HMM was trained using "signature" and the values seem to be intuitive. My question is more a fundamental one in regards to understanding HMMs. I know I should use more examples of the above sequences to train the HMM in order to make it more robust. Assuming, that the HMM is trained good enough, I can use the viterbi algorithm to find the most probable sequence of hidden states. However, what I really want to find out is whether a partic...
2017 Aug 31
0
The aphid package for analysis with profile hidden Markov models
...the DNAbin or AAbin format), model building, parameter optimization (Baum Welch and Viterbi training), plotting, file import & export, tree-based sequence weighting, simulation, and implementation of the forward, backward and Viterbi algorithms for calculating sequence probabilities. Standard HMMs are also supported, with functions for building, training, plotting, sequence simulation, and HMM implementations of the forward, backward & Viterbi algorithms. The package has a wide variety of uses including database searching, gene-finding and annotation, phylogenetic analysis and sequence...
2017 Aug 31
0
The aphid package for analysis with profile hidden Markov models
...the DNAbin or AAbin format), model building, parameter optimization (Baum Welch and Viterbi training), plotting, file import & export, tree-based sequence weighting, simulation, and implementation of the forward, backward and Viterbi algorithms for calculating sequence probabilities. Standard HMMs are also supported, with functions for building, training, plotting, sequence simulation, and HMM implementations of the forward, backward & Viterbi algorithms. The package has a wide variety of uses including database searching, gene-finding and annotation, phylogenetic analysis and sequence...
2011 Apr 17
2
RJMCMC.
Dear R users, I´m studying about Bayesian Statistics. In this context, please, anyone have some basic script of RJMCMC (Reversible Jump Markov chain Monte Carlo) in R or WinBUGS? My aim is to learn how to implement this methodology. Thanks a lot. Marcus Vinicius [[alternative HTML version deleted]]
2023 Jun 25
1
depmixs4 standardError() issue
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
2009 Jun 16
0
ANNOUNCEMENT: 20% discount on the most recent R books from Chapman & Hall/CRC!
...t/isbn/9781420065176 *** Hidden Markov Models for Time Series: An Introduction Using R Walter Zucchini, University of Gottingen, Germany and Iain L. MacDonald, University of Cape Town, South Africa Publication Date: April 2009 Number of Pages: 288 This book applies hidden Markov models (HMMs) to a wide range of time series types, from continuous-valued, circular, and multivariate series to binary data, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out computations for parameter estimatio...