scoreConfoundersComp: Score equations for conditioning under compositionality

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

Score equations for conditioning under compositionality

Description

Score equations for conditioning under compositionality

Usage

scoreConfoundersComp(
  x,
  confMat,
  data,
  meanVarTrend,
  marginModel,
  biasReduction,
  allowMissingness,
  subtractMax = TRUE
)

Arguments

x	Confounder parameter estimates
confMat	confounder matrix
data	data
meanVarTrend	mean variance trend
marginModel	marginal models
biasReduction	A boolean, should a bias reduced estimation be applied?
allowMissingness	A boolean, are missing values allowed
subtractMax	A boolean, shuold the maximum be subtracted before softmax transformation? Recommended for numerical stability

Value

The evaluation of the estimating equations

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