derivLagrangianLatentVarsConstr: The score function to estimate the latent variables

View source: R/derivLagrangianLatentVarsConstr.R

derivLagrangianLatentVarsConstrR Documentation

The score function to estimate the latent variables

Description

The score function to estimate the latent variables

Usage

derivLagrangianLatentVarsConstr(
  x,
  data,
  distributions,
  offsets,
  paramEsts,
  numVars,
  latentVarsLower,
  n,
  m,
  numSets,
  meanVarTrends,
  links,
  covMat,
  numCov,
  centMat,
  nLambda1s,
  varPosts,
  compositional,
  indepModels,
  paramMats,
  ...
)

Arguments

x

The current estimates of the latent variables

latentVarsLower

The parameter estimates of the lower dimensions

n

The number of samples

m

The dimensions

numSets

The number of views

covMat

The covariance matrix

numCov

The number of covariates

centMat

A centering matrix

nLambda1s

The number of dummy variables

compositional, links, indepModels, meanVarTrends, numVars, distributions, data, offsets, varPosts, paramMats, paramEsts

Lists of information 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/combi documentation built on Aug. 22, 2023, 11:02 p.m.