faPredict: Predict new values, given the parameters of a trained FA...

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 FA model

Usage

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

Arguments

p	parameters of a fitted FA
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 <- faFit(X_t_unsupervised = house[1:20,2:3,drop=FALSE],
                paramsNULL_nDimZ = 2,
                params=NULL,
                type="fa",
                lambdaRidge=0,
                checkArgs=FALSE,
                checkPositiveDefinite=FALSE,
                epsilon=1e-10,
                maxIterations=100,
                stopType="parameter",
                turboEmMethods=NULL)
result <- faPredict(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.