Multivariate and Multichannel Discrete Hidden Markov Models for Categorical Sequences
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Updated
Sep 16, 2024 - R
Multivariate and Multichannel Discrete Hidden Markov Models for Categorical Sequences
Full Bayesian Inference for Hidden Markov Models
StAtistical Models for the UnsupeRvised segmentAion of tIme-Series
An R package for analysis of Markov Random Fields on 2-dimensional lattices.
Travel time prediction from GPS observations using an HMM
Functional Latent datA Models for clusterING heterogeneOus curveS
R script to modelize a tennis match with Markov chains (games, tie-breaks, sets, match)
Compute a phylogeny using EggNOG database
Infer blocks of identity by descent between samples from unphased haplotype data using an HMM
The code interface is written in R, and for the sake of speed, most parts are written in C++. However, no prerequisite knowledge for both languages is required to run the code. An R file called runInfHMM.R sources all needed functions to compile and run the code.
Here, I am going to present important findings on Hidden Markov Models related to my studies on the field. So, basically I will present the majority of codes that I am using to understand the theory
An R package to identify plant transcription factors from protein sequence data and classify them in families
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