s3faPredict: Predict new values, given the parameters of a trained S3FA...

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 S3FA model

Usage

s3faPredict(p, X_t_test, checkArgs = TRUE,
  checkPositiveDefinite = FALSE)

Arguments

p	parameters of a fitted S3FA
X_t_test	a matrix containing the input data; their output values would be predicted
checkArgs	whether to check the arguments are valid; it takes more time to execute
checkPositiveDefinite	whether to check the covariance matrices are valid; it takes more time to execute

Value

a list containing the transposed predicted values ($values_t) and the covariance matrix associated with them ($Sigma_t)

Examples

params <- s3faFit(X_t_supervised = house[1:10,2:3,drop=FALSE],
                  Z_t_supervised = house[1:10,1,drop=FALSE],
                  X_t_unsupervised = house[11:20,2:3,drop=FALSE],
                  params=NULL,
                  type="fa",
                  lambdaRidge=0,
                  checkArgs=FALSE,
                  checkPositiveDefinite=FALSE,
                  epsilon=1e-10,
                  maxIterations=100,
                  stopType="objfn",
                  turboEmMethods=NULL)
result <- s3faPredict(p = params,
                      X_t_test = house[11:20,2:3,drop=FALSE],
                      checkArgs=TRUE,
                      checkPositiveDefinite=FALSE)
result

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