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HiddenMarkov

Hidden Markov Models

Contains functions for the analysis of Discrete Time Hidden Markov Models, Markov Modulated GLMs and the Markov Modulated Poisson Process. It includes functions for simulation, parameter estimation, and the Viterbi algorithm. See the topic "HiddenMarkov" for an introduction to the package, and "Change Log" for a list of recent changes. The algorithms are based of those of Walter Zucchini.

Functions (27)

Estimation Using Baum-Welch Algorithm

Changes Made to Package HiddenMarkov

Demonstration

Demonstration Examples

E-Step of EM Algorithm for DTHMM

HiddenMarkov

Overview of Package HiddenMarkov

HiddenMarkov-defunct

Defunct Functions in Package HiddenMarkov

HiddenMarkov-dthmm-deprecated

Discrete Time HMM - Deprecated Functions

HiddenMarkov-internal

Internally Used Functions

HiddenMarkov-mmpp-deprecated

Markov Modulated Poisson Process - Deprecated Functions

M-Step of EM Algorithm for DTHMM

Transform-Parameters

Transform Transition or Rate Matrices to Vector

Viterbi Algorithm for Hidden Markov Model

Control Parameters for Baum Welch Algorithm

Marginal Distribution of Stationary Markov Chain

Discrete Time HMM Object (DTHMM)

forwardback

Forward and Backward Probabilities of DTHMM

Log Likelihood of Hidden Markov Model

Markov Chain Object

Markov Modulated GLM Object

mmglm-2nd-level-functions

Markov Modulated Generalised Linear Model - 2nd Level Functions

mmpp

Markov Modulated Poisson Process Object

mmpp-2nd-level-functions

Markov Modulated Poisson Process - 2nd Level Functions

Negative Log-Likelihood

Conditional Distribution Function of DTHMM

Residuals of Hidden Markov Model

Simulate Hidden Markov Process

Summary of Hidden Markov Model

HiddenMarkov

Hidden Markov Models

v1.8-13

GPL (>= 2)

Authors

David Harte

Initial release

2021-04-27

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