HurdleStructure: Structure to hold a model, samples and estimates

In amcdavid/HurdleNormal: 'Estimation and sampling for multi-dimensional Hurdle models on a Normal density with applications to single-cell co-expression'

Structure to hold a model, samples and estimates

Description

Structure to hold a model, samples and estimates

Usage

HurdleStructure(
  G = NULL,
  H = NULL,
  K = NULL,
  sample = NULL,
  gibbs = TRUE,
  estimate = NULL,
  gibbs_args = list(kcell = 1, mvnorm = FALSE)
)

Arguments

G	symmetric discrete interaction matrix
H	unstructured location matrix
K	Symmetric positive definite conditional precision matrix
sample	optional sample from the model
gibbs	If TRUE, then sample from the provided model. Else may contain a sample from the model
estimate	optional estimated coefficients (replaces provided G, H, K if provided).
gibbs_args	list of arguments passed to getGibbs

Value

list with the above components

Author(s)

Andrew McDavid

amcdavid/HurdleNormal documentation built on May 14, 2022, 11:12 p.m.