prac: An example with M=10 (basis functions) and r=5 (non-zero...

In fpca: Restricted MLE for Functional Principal Components Analysis

Description

A simulated dataset as an example which corresponds to the "practical" case in the paper

Usage

data(prac)

Format

prac is a list with six components (in the given order):

data

data matrix with three columns: column 1–ID, column 2–measurement, column 3–time.

eigenfunctions

true eigenfunctions: generated from cubic Bsplines with M=10 equally spaced knots.

eigenvalues

true eigenvalues: first–1, second–0.66, third–0.52, fourth–0.44, fifth–0.38, others–zero.

number_of_basis

true number of basis functions: M=10.

dimension

true dimension of the process: r=5.

error_sd

true error standard deviation: 0.25.

Details

mean curve of the process is zero; principal component scores and errors are all i.i.d N(0,1); there are 500 subjects, and each has 2~10 measurements uniformly distributed on [0,1]; in total there are 3018 measurements

fpca documentation built on May 1, 2019, 10:26 p.m.