gsFPCA: Function for modeling single-level fpca

In acweisha/gFPCAClassif: Classification of Binary Functional Data

Description

Function for modeling single-level fpca

Usage

gsFPCA(
  X_dat_s,
  Ys,
  covariates = NA,
  pve = 0.95,
  Kb = 10,
  num_knots = 10,
  bs0 = "cr"
)

Arguments

X_dat_s	N x m matrix of binary data
Ys	N long vector of groups
covariates	N x Q data frame of covariates
pve	Proportion of variation explained
Kb	number of basis functions used when estimating latent trajectories
num_knots	number of knots in basis functions
bs0	type of basis functions used when estimating latent trajectories

Value

list of information required to build the model and predict new groups

acweisha/gFPCAClassif documentation built on Dec. 18, 2021, 10:23 p.m.