
SHOGUN
 Referenced in 103 articles
[sw03517]
 models such as support vector machines, hidden Markov models, multiple kernel learning, linear discriminant analysis...

msm
 Referenced in 50 articles
[sw08096]
 package msm: Multistate Markov and hidden Markov models in continuous time. Functions for fitting ... general continuoustime Markov and hidden Markov multistate models to longitudinal data. A variety ... transition rates and the hidden Markov output process can be modelled in terms of covariates...

PRISM
 Referenced in 34 articles
[sw23359]
 most popular probabilistic modeling formalisms, the hidden Markov model and Bayesian networks, are described...

Rfam
 Referenced in 33 articles
[sw04637]
 sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down ... more complicated relative of the profile hidden Markov models (HMMs) used by Pfam...

LSTM
 Referenced in 28 articles
[sw03373]
 than other adaptive approaches such as Hidden Markov Models (no continuous internal states), feedforward networks...

WAFO
 Referenced in 25 articles
[sw07370]
 loads; Theoretical density of rainflow cycles Sea modelling: Simulation of linear and nonlinear Gaussian ... Extreme value analysis; Kernel density estimation, Hidden markov models...

moveHMM
 Referenced in 13 articles
[sw16166]
 using Hidden Markov Models. Provides tools for animal movement modelling using hidden Markov models. These ... include processing of tracking data, fitting hidden Markov models to movement data, visualization of data...

depmixS4
 Referenced in 14 articles
[sw08234]
 package depmixS4: Dependent Mixture Models  Hidden Markov Models of GLMs and Other Distributions ... latent (hidden) Markov models on mixed categorical and continuous (time series) data, otherwise known...

Label.switching
 Referenced in 20 articles
[sw14745]
 mixture models (and more general hidden Markov models) suffers from the label switching phenomenon, making...

PennCNV
 Referenced in 16 articles
[sw19390]
 PennCNV: an integrated hidden Markov model designed for highresolution copy number variation detection ... kilobases. Here we present PennCNV, a hidden Markov model (HMM) based approach, for kilobaseresolution...

HTK
 Referenced in 15 articles
[sw07937]
 Hidden Markov Model Toolkit (HTK) is a portable toolkit for building and manipulating hidden Markov...

MALLET
 Referenced in 21 articles
[sw10602]
 natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications ... entity extraction from text. Algorithms include Hidden Markov Models, Maximum Entropy Markov Models, and Conditional...

hmm
 Referenced in 14 articles
[sw05422]
 hidden Markov model (HMM) is one in which you observe a sequence of emissions ... generate the emissions. Analyses of hidden Markov models seek to recover the sequence of states...

HiddenMarkov
 Referenced in 14 articles
[sw08010]
 package HiddenMarkov: Hidden Markov Models. Contains functions for the analysis of Discrete Time Hidden Markov...

PITA
 Referenced in 20 articles
[sw06950]
 form of programs needed to model problems, and on the scale of the problems ... with PRISM for complex queries to Hidden Markov Model examples, and sometimes much faster...

HMMER
 Referenced in 19 articles
[sw10514]
 feasible to make efficient profile hidden Markov model (profile HMM) searches...

BioHMM
 Referenced in 13 articles
[sw10920]
 BioHMM: a heterogeneous hidden Markov model for segmenting array CGH data. Summary: We have developed ... copy number. By utilizing a heterogeneous hidden Markov model, BioHMM incorporates relevant biological factors...

Statistics Toolbox
 Referenced in 18 articles
[sw10157]
 identify key variables that impact your model with sequential feature selection, transform your data with ... nearest neighbor search, Gaussian mixtures, and hidden Markov models...

hsmm
 Referenced in 17 articles
[sw00419]
 package hsmm: Hidden Semi Markov Models: This package allows for the simulation and maximum likelihood ... estimation of hidden semiMarkov models. The implemented Expectation Maximization algorithm assumes that the time...

TileMap
 Referenced in 14 articles
[sw35530]
 interest or not. Hierarchical empirical Bayes model shrinks variance estimates and increases sensitivity ... moving average method (MA) or a hidden Markov model (HMM). Unbalanced mixture subtraction is proposed...