intervalPOFD: Random Interval Observability

In fdaPOIFD: Partially Observed Integrated Functional Depth

Random Interval Observability

Description

Generates samples of functions observed in different intervals. See Elías et al (2020).

Usage

intervalPOFD(data, observability = NULL, ninterval = NULL, pIncomplete = NULL)

Arguments

data	functional data completely observed. pxn matrix being n the number of curves and p the number og evaluation points.
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.
pIncomplete	number between 0 and 1 related to the proportion of curves that suffers partially observability. The default is 1 meaning that all the sample curves are partially observed.

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

Elías, Antonio, Jiménez, Raúl, Paganoni, Anna M. and Sangalli, Laura M. (2020). Integrated Depths for Partially Observed Functional Data.

Examples

data <- sapply(1:100, function(x) runif(1)*sin(seq(0, 2*pi, length.out = 200)) +
runif(1)*cos(seq(0, 2*pi, length.out = 200)))

data_pofd <- intervalPOFD(data, observability = 0.5, ninterval = 2, pIncomplete = 1)

fdaPOIFD documentation built on May 16, 2022, 5:05 p.m.