estFeatureParameters: Estimate the feature parameters

View source: R/estFeatureParameters.R

estFeatureParametersR Documentation

Estimate the feature parameters

Description

Estimate the feature parameters

Usage

estFeatureParameters(
  paramEsts,
  lambdasParams,
  seqSets,
  data,
  distributions,
  offsets,
  nCores,
  m,
  JacFeatures,
  meanVarTrends,
  latentVars,
  numVars,
  control,
  weights,
  compositional,
  indepModels,
  fTol,
  allowMissingness,
  maxItFeat,
  ...
)

Arguments

paramEsts

Current list of parameter estimates for the different views

lambdasParams

The lagrange multipliers

seqSets

A vector with view indices

data

A list of data matrices

distributions

A character vector describing the distributions

offsets

A list of offset matrices

nCores

The number of cores to use in multithreading

m

The dimension

JacFeatures

An empty Jacobian matrix

meanVarTrends

The mean-variance trends of the different views

latentVars

A vector of latent variables

numVars

The number of variables

control

A list of control arguments for the nleqslv function

weights

The normalization weights

compositional

A list of booleans indicating compositionality

indepModels

A list of independence model

fTol

A convergence tolerance

allowMissingness

A boolean indicating whether missing values are allowed

maxItFeat

An integer, the maximum number of iterations

...

Additional arguments passed on to the score and jacobian functions

Value

A vector with estimates of the feature parameters


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