deriv2LagrangianLatentVars: The jacobian function to estimate the latent variables

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

The jacobian function to estimate the latent variables

Description

The jacobian function to estimate the latent variables

Usage

deriv2LagrangianLatentVars(
  x,
  data,
  distributions,
  offsets,
  paramEsts,
  paramMats,
  numVars,
  latentVarsLower,
  n,
  m,
  Jac,
  numSets,
  meanVarTrends,
  links,
  varPosts,
  indepModels,
  compositional,
  ...
)

Arguments

x	The current estimates of the latent variables
distributions, links, compositional, data, meanVarTrends, offsets, numVars, numSets, paramMats, paramEsts, varPosts, indepModels	Characteristics of the views
latentVarsLower	The parameter estimates of the lower dimensions
n, m	integers, number of samples and dimensions
Jac	an empty jacobian matrix
...	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.