controlEM: Control parameters for the EM algorithm from epigraHMM

In plbaldoni/epigraHMM: Epigenomic R-based analysis with hidden Markov models

Control parameters for the EM algorithm from epigraHMM

Description

This function passes controlling parameters for the EM algorithm implemented in the epigraHMM package.

Usage

controlEM(
  epsilonEM = c(MRCPE = 0.001, MACPE = 0.001, ARCEL = 0.001),
  maxIterEM = 500,
  minIterEM = 3,
  gapIterEM = 3,
  maxCountEM = 3,
  maxDisp = 1000,
  criterion = "all",
  minZero = .Machine$double.xmin,
  probCut = 0.05,
  quiet = TRUE,
  maxIterInnerEM = 5,
  epsilonInnerEM = 0.001,
  trimOffset = 3,
  pattern = NULL,
  tempDir = tempdir(),
  fileName = "epigraHMM",
  pruningThreshold = NULL,
  quietPruning = TRUE
)

Arguments

epsilonEM	a named vector of positive values specifying up to four possible convergence criterion tolerances for the EM algorithm (see 'criterion' below). Default is c('MRCPE' = 1e-3, 'MACPE' = 1e-3,'ARCEL' = 1e-3).
maxIterEM	a positive integer giving the maximum number of EM iterations. Default is 500.
minIterEM	a positive integer giving the minimum number of EM iterations to start evaluating the convergence. Default is 3.
gapIterEM	a positive integer giving the number of EM iterations apart to compute the convergence criterion. Default is 3.
maxCountEM	a positive integer giving the number of consecutive EM iterations satisfying the convergence criterion in order to stop the algorithm. Default is 3.
maxDisp	a positive value for the upper limit constraint of the dispersion parameters. Default is 1000.
criterion	a character specifying the convergence criterion. Either "MRCPE" (maximum absolute relative change in parameter estimates), "MACPE" (maximum absolute change of parameter estimates), "ARCEL" (absolute relative change of the Q-function), or "all" (simultaneously check for MRCPE, MACPE, and ARCEL). Default is "all".
minZero	a positive value for the minimum positive value allowed in computations to avoid having zeros. Default is .Machine$double.xmin.
probCut	a number between 0 and 1 for the cutoff of the rejection controlled EM algorithm. Default 0.05.
quiet	a logical indicating whether to print messages. Default is TRUE.
maxIterInnerEM	a positive integer giving the maximum number of inner EM iterations. Default is 5.
epsilonInnerEM	a positive value with the convergence tolerance value for the inner EM algorithm. The criterion for the inner EM is "MRCPE". Default is 1e-3.
trimOffset	either NULL or a positive integer indicating the number of decimal places to be used in the offset. Default is 3.
pattern	either NULL (the default) or a list with length equal to the number of differential patterns to be modeled by the differential HMM state. See Details section below.
tempDir	a string where results will be saved. Default is 'tempdir()'.
fileName	a string with the name of the result files. Default is 'epigraHMM'.
pruningThreshold	a numeric value between 0 and 1 to consider when pruning rare combinatorial patterns. Default is NULL (see Details).
quietPruning	a logical indicating whether to print messages during the pruning step. Default is TRUE.

Details

If pattern is NULL, every possible combinatorial pattern will be considered. If pattern is a list, elements of it should specify the differential patterns to be modeled by each mixture component. For instance, if pattern = list(2,c(1,3)) the mixture model will have two components that will represent the enrichment of condition 2 alone and the enrichment of conditions 1 and 3 together.

If pruningThreshold is a value between 0 and 1, say 0.05, epigraHMM will sequentially remove differential combinatorial patterns of enrichment from any mixture model component with associated posterior mixture proportion less than 0.05.

Value

A list with components equal to the arguments

Author(s)

Pedro L. Baldoni, [e-mail]

References

https://github.com/plbaldoni/epigraHMM

Examples

# No more than 100 EM iterations
control <- controlEM(maxIterEM = 100)

plbaldoni/epigraHMM documentation built on Oct. 15, 2023, 7:53 p.m.