deriv2LagrangianLatentVarsConstr: The score function to estimate the latent variables

View source: R/deriv2LagrangianLatentVarsConstr.R

deriv2LagrangianLatentVarsConstrR Documentation

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