fdaPOIFD (version 1.0.0)

gaussian_PoFD: Gaussian Partially Observed Functional Data

Description

Generates samples of partially observed gaussian functions following different censoring regimes.

Usage

gaussian_PoFD(n, p, type, observability, ninterval)

Arguments

n

total number of functional observations

p

total number of points observed for each function

type

type of partially observed data. Options are "sparse", "interval" and "common". See El<U+00ED>as et al (2020).

observability

mean observed proportion of the domain where each function is observed.

ninterval

if type = "interval", n_interval is an integer with the number of observed intervals 1, 2, 3... Large values of this parameter requires a large parameter p to guarantee the observability level.

Value

a list containing two elements 1) a functional sample and 2) the same sample of functions but partially observed following one of the schemes described in the argument type.

References

El<U+00ED>as, Antonio, Jim<U+00E9>nez, Ra<U+00FA>l, Paganoni, Anna M. and Sangalli, Laura M. (2020). Integrated Depths for Partially Observed Functional Data.

Examples

# NOT RUN {
gaussian_pofd <- gaussian_PoFD(n=100, p=200, type="sparse", observability=0.5)

# }