Usage
fitHMM(obs=list(), hmm, convergence=1e-06, maxIters=1000, dirFlags=list(), emissionProbs=list(), effectiveZero=0, verbose=FALSE, nCores=1, incrementalEM=FALSE, observationEmissionType=c())
Arguments
obs
The observations. A list of one or more entries containing the observation matrix (numeric) for the samples (e.g. chromosomes).
hmm
The initial Hidden Markov Model. This is a HMM.
convergence
Convergence cutoff for EM-algorithm (default: 1e-6).
maxIters
Maximum number of iterations.
dirFlags
The flag sequence is needed when a bdHMM is fitted on undirected data (e.g.) ChIP only. It is a list of character vectors indication for each position its knwon directionality. U allows all states. F allows undirected states and states in forward direction. R allows undirected states and states in reverse direction.
emissionProbs
List of precalculated emission probabilities of emission function is of type 'null'.
effectiveZero
Transitions below this cutoff are analytically set to 0 to speed up comptuations.
verbose
logical for printing algorithm status or not.
nCores
Number of cores to use for computations.
incrementalEM
When TRUE, the incremental EM is used to fit the model, where parameters are updated after each iteration over a single observation sequence.
observationEmissionType
Only needed when HMMEmission is 'JointlyIndependent'. Defines for each dimension (columns in obs) of the data the type of emission to be used.