deriv2LagrangianLatentVarsConstr: 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

deriv2LagrangianLatentVarsConstr(
  x,
  data,
  distributions,
  offsets,
  paramEsts,
  paramMats,
  numVars,
  latentVarsLower,
  nn,
  m,
  Jac,
  numSets,
  meanVarTrends,
  links,
  numCov,
  covMat,
  nLambda1s,
  varPosts,
  compositional,
  indepModels,
  ...
)

Arguments

x	The current estimates of the latent variables
distributions, data, links, compositional, meanVarTrends, offsets, numVars, paramMats, paramEsts	Characteristics of the view
latentVarsLower	The parameter estimates of the lower dimensions
nn	number of samples
m, numSets, varPosts, indepModels	other arguments
Jac	an empty jacobian matrix
numCov	The number of covariates
covMat	the covariates matrix
nLambda1s	The number of centering restrictions
...	arguments to the jacobian function, currently ignored

Value

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

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