backwardAlg: backwardAlg
In jiangrongo/HMM:

backwardAlg performs the Backward Algorithm on a single trajecture of observed chain X

1	backwardAlg(X, trans, u, sig)

`X`	a vector of observed states
`trans`	a matrix of transition probability
`u`	a vector of means of Normal distribution for each state (emission probability)
`sig`	a vector of standard deviations of Normal distribution for each state (emission probability)

backwardAlg computes the matrix, beta, where beta[k,t] = P(X[(t+1):T]=x[(t+1):T] | Z[t]=k)

A matrix, beta.

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set.seed(1221)
df <- generateHMM(num=2,n=10)
backwardAlg(df$X[,1], df$trans, df$u, df$sig)

jiangrongo/HMM documentation built on May 19, 2019, 9:38 p.m.

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