mS3faPredict: Predict new values, given the parameters of a trained MS3FA...

In aciobanusebi/s2fa: Factor Analysis (FA), Simple Supervised FA (S2FA), Simple Semi-Supervised FA (S3FA), Missing S3FA (MS3FA)

Description

Predict new values, given the parameters of a trained MS3FA model

Usage

mS3faPredict(params, testInput, testOutput)

Arguments

params	parameters of a fitted MS3FA
testInput	test input data; can contain NAs; error if a full row (input+output) is NA
testOutput	train output data; can contain NAs; error if a full row (input+output) is NA

Value

a list with two elements: '$values' only with imputed NAs, '$Sigmas' with the covariance matrices associated with them (one for each)

Examples

houseCopy <- house
houseCopy[1:10,2:3] <- NA
houseCopy[11:20,1] <- NA
params <- mS3faFit(trainInput=houseCopy[,2:3,drop=FALSE],
                   trainOutput=houseCopy[,1,drop=FALSE],
                   params=NULL,
                   type="ppca",
                   lambdaRidge=0,
                   epsilon=1e-10,
                   maxIterations=100,
                   stopType="objfn",
                   turboEmMethods=NULL)
result <- mS3faPredict(params=params,
                       testInput=houseCopy[,2:3,drop=FALSE],
                       testOutput=houseCopy[,1,drop=FALSE])
result

aciobanusebi/s2fa documentation built on Aug. 7, 2021, 6:38 a.m.