derivLagrangianLatentVars: The score function to estimate the latent variables

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

The score function to estimate the latent variables

Description

The score function to estimate the latent variables

Usage

derivLagrangianLatentVars(
  x,
  data,
  distributions,
  offsets,
  paramEsts,
  paramMats,
  numVars,
  n,
  m,
  numSets,
  meanVarTrends,
  links,
  varPosts,
  latentVarsLower,
  compositional,
  indepModels,
  ...
)

Arguments

x	The current estimates of the latent variables
n	The number of samples
m	The dimensions
numSets	The number of views
latentVarsLower	The parameter estimates of the lower dimensions
compositional, links, indepModels, meanVarTrends, numVars, distributions, data, offsets, varPosts, paramMats, paramEsts	Lists of inforamtion on all the views
...	arguments to the jacobian function, currently ignored

Value

A vector of length n, the evaluation of the score functions of the latent variables

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