derivLagrangianLatentVarsConstr: 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

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

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