estFeatureParameters: Estimate the feature parameters

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

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.