ifpca: Intensity Functional Principal Component Analysis (IFPCA)
In celehs/IFPCA: Intensity Functional Principal Component Analysis (IFPCA)

Performs IFPCA to extract features from longitudinal encounter data.

1	ifpca(time, fu_train, fu_valid, PPIC_K = FALSE, n.grid = 401, propvar = 0.85)

`time`	longitudinal encounter times
`fu_train`	follow-up time (training)
`fu_valid`	follow-up time (validation)
`PPIC_K`	a logical indicating whether you want to use Pseudo-Poisson Information Criterion to choose the number of principal components K (K.select="PPIC") `TRUE` or another criterion to choose K (K.select="PropVar") `FALSE` in the PP_FPCA_Parallel function (hidden). Default is `FALSE`.
`n.grid`	an integer value for grid points used in estimating covariance function g. Default is `401`.
`propvar`	a proportion of variation used to select number of FPCs. Default is `0.85`.