deriv2LagrangianLatentVarsConstr: The score function to estimate the latent variables

In combi: Compositional omics model based visual integration

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
data	Lists of inforamtion on all the views
distributions, links, compositional, meanVarTrends, offsets, numVars, paramMats, paramEsts	Characteristics of the view
latentVarsLower	The parameter estimates of the lower dimensions
nn	number of samples
m	integeres, number of samples and dimensions
Jac	an empty jacobian matrix
numSets	Characteristics of the views
numCov	The number of covariates
covMat	the covariates matrix
nLambda1s	The number of centering restrictions
varPosts	Characteristics of the views
indepModels	Characteristics of the views
...	arguments to the jacobian function, currently ignored

Value

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

combi documentation built on Nov. 8, 2020, 5:34 p.m.