derivLagrangianFeatures: The score function to estimate the feature parameters

In CenterForStatistics-UGent/compIntegrate: Compositional omics model based visual integration

The score function to estimate the feature parameters

Description

The score function to estimate the feature parameters

Usage

derivLagrangianFeatures(
  x,
  data,
  distribution,
  offSet,
  latentVars,
  numVar,
  paramEstsLower,
  mm,
  indepModel,
  meanVarTrend,
  weights,
  compositional,
  ...
)

Arguments

x	current parameter estimates
data	A list of data matrices
distribution, compositional, meanVarTrend, offSet, numVar, indepModel, paramEstsLower	Characteristics of the view
latentVars	A vector of latent variables
mm	the current dimension
weights	The normalization weights
...	arguments to the jacobian function, currently ignored

Value

A vector with the evaluation of the score functions of the feature parameters

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