beta_function: Normalized Backward Probability function EM

In pneff93/HMM: Fitting a Hidden Markov Model

Description

This function calculates the normalized backward probability of the HMM states. For this the function needs the weights of the forward probability, which have to be inputed as parameter weight. In the general literatur also revered to as beta matrix.

Usage

beta_function(m, N, Gamma, p, set, weight)

Arguments

m	number of likelihoods
N	length of the supplied dataset
Gamma	Gamma matrix
p	vector of likelihood probabilities of the dataset
set	index vector to align the p vector
weight	weights provided by the alpha calculation

Value

Returns the beta as a matrix with the dimensions m as rows and the datapoints t as columns.

pneff93/HMM documentation built on Oct. 26, 2019, 8:16 a.m.