Full Bayesian Inference for Hidden Markov Models
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Updated
Jan 14, 2019 - R
Full Bayesian Inference for Hidden Markov Models
Compute a phylogeny using EggNOG database
StAtistical Models for the UnsupeRvised segmentAion of tIme-Series
Functional Latent datA Models for clusterING heterogeneOus curveS
R script to modelize a tennis match with Markov chains (games, tie-breaks, sets, match)
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
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.
Infer blocks of identity by descent between samples from unphased haplotype data using an HMM
Travel time prediction from GPS observations using an HMM
An R package for analysis of Markov Random Fields on 2-dimensional lattices.
An R package to identify plant transcription factors from protein sequence data and classify them in families
Multivariate and Multichannel Discrete Hidden Markov Models for Categorical Sequences
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