scoreLatentVars: Evaluate the score functions for the estimation of the latent...

In CenterForStatistics-UGent/compIntegrate: Compositional omics model based visual integration

Evaluate the score functions for the estimation of the latent variables for a single dataset

Description

Evaluate the score functions for the estimation of the latent variables for a single dataset

Usage

scoreLatentVars(
  data,
  distribution,
  paramEsts,
  paramMats,
  offSet,
  latentVar,
  meanVarTrend,
  constrained = FALSE,
  covMat = NULL,
  varPosts,
  compositional,
  indepModel,
  mm,
  latentVarsLower,
  allowMissingness,
  ...
)

Arguments

data, distribution, offSet, meanVarTrend, indepModel, varPosts, paramEsts, paramMats, compositional	Characteristics of the views
latentVar	the latent variable estimates
constrained	a boolean, is this a constrained analysis
covMat	a matrix of constraining covariates
mm	the current dimension
latentVarsLower	the lower dimensional latent variables
allowMissingness	a boolean, should missing values be allowed
...	additional arguments passed on to score and jacobian functions

Value

A vector of length n, with evaluated score function

CenterForStatistics-UGent/compIntegrate documentation built on Aug. 4, 2023, 1:08 p.m.