expStep {epigraHMM} | R Documentation

## E-step of HMM (forward-backward probability + posterior probability calculation)

### Description

E-step of HMM (forward-backward probability + posterior probability calculation)

### Usage

    expStep(pi, gamma, logf, hdf5)

### Arguments

`pi` | a vector of probabilities (sum of probabilities should sum to one)
`gamma` | a matrix of transition probabilities (row sums should be one)
`logf` | a matrix of observed log-likelihood values. Columns represent hidden states, rows represent genomic regions
`hdf5` | path to where the hdf5 is saved

### Examples

    #Creating dummy object
    countData <- rbind(matrix(rnbinom(1e3,mu = 2,size = 10),ncol = 1),
                      matrix(rnbinom(2e3,mu = 7.5,size = 5),ncol = 1),
                      matrix(rnbinom(1e3,mu = 2,size = 10),ncol = 1))

    colData <- data.frame(condition = 'A', replicate = 1)
    object <- epigraHMMDataSetFromMatrix(countData,colData)

    #Initializing
    object <- initializer(object,controlEM())

    #Running epigraHMM
    object <- epigraHMM(object,controlEM(),type = 'consensus',dist = 'nb')

    #Example
    expStep(pi = c(0.99,0.02),
           gamma = matrix(c(0.99,0.01,0.01,0.99),nrow = 2),
           logf = cbind(dnbinom(rnbinom(100,mu = 2,size = 10),mu = 2,size = 10,log = TRUE),
                        dnbinom(rnbinom(100,mu = 7.5,size = 5),mu = 7.5,size = 5,log = TRUE)),
           hdf5 = file.path(tempdir(),'tmp.h5'))

[Package epigraHMM version 1.0.8 Index]