s2faPredict: Predict new values, given the parameters of a trained S2FA...

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 S2FA model

Usage

s2faPredict(p, X_t_test, checkArgs = TRUE,
  checkPositiveDefinite = FALSE)

Arguments

p	parameters of a fitted S2FA
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 <- s2faFit(X_t=house[,2:3,drop=FALSE],
                  Z_t=house[,1,drop=FALSE],
                  type = "fa",
                  lambdaRidge=0,
                  checkArgs=FALSE)
result <- s2faPredict(p = params,
                    X_t_test = house[21:26,2:3,drop=FALSE],
                    checkArgs=TRUE,
                    checkPositiveDefinite=FALSE)
result

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