computeObservationalWeights {zinbwave} | R Documentation |
Given a matrix of counts, this function computes the observational weights of the counts under a zero-inflated negative binomial (ZINB) model. For each count, the ZINB distribution is parametrized by three parameters: the mean value and the dispersion of the negative binomial distribution, and the probability of the zero component.
computeObservationalWeights(model, x)
model |
the zinb model |
x |
the matrix of counts |
the matrix of observational weights computed from the model.
se <- SummarizedExperiment(matrix(rpois(60, lambda=1), nrow=10, ncol=6), colData = data.frame(bio = gl(2, 3))) m <- zinbFit(se, X=model.matrix(~bio, data=colData(se)), BPPARAM=BiocParallel::SerialParam()) computeObservationalWeights(m, assay(se))