obs.loglikelihood: Observed Log-Likelihood

In cbg-ethz/MC-CBN: Large-scale inference of continuous time Conjunctive Bayesian Networks

Observed Log-Likelihood

Description

compute the observed log-likelihood

Usage

obs.loglikelihood(
  obs,
  poset,
  lambda,
  eps,
  weights = NULL,
  times = NULL,
  L,
  sampling = c("forward", "add-remove", "backward", "bernoulli", "pool"),
  neighborhood.dist = 1L,
  lambda.s = 1,
  thrds = 1L,
  seed = NULL
)

Arguments

obs	a matrix containing observations or genotypes, where each row correponds to a genotype vector whose entries indicate whether an event has been observed (1) or not (0)
poset	a matrix containing the cover relations
lambda	a vector of the rate parameters
eps	error rate
weights	an optional vector containing observation weights
times	an optional vector of sampling times per observation
L	number of samples to be drawn from the proposal
sampling	sampling scheme to generate hidden genotypes, X. OPTIONS: "forward", "add-remove", "backward", "bernoulli", or "pool"
neighborhood.dist	an integer value indicating the Hamming distance between the observation and the samples generated by "backward" sampling. This option is used if sampling is set to "backward". Defaults to 1
lambda.s	rate of the sampling process. Defaults to 1.0
thrds	number of threads for parallel execution
seed	seed for reproducibility

cbg-ethz/MC-CBN documentation built on Dec. 15, 2022, 5:42 p.m.