m.dev: Deviations from functional linearity

In egarpor/rp.flm.test: Goodness-of-fit Test for the Functional Linear Model with Scalar Response Based on Random Projections

Description

Deviations from functional linearity considered in the simulation study of Cuesta-Albertos et al. (2019).

Usage

m.dev(X.fdata, type, delta, eta, composite = TRUE)

Arguments

X.fdata	functional observations in the class fdata.
type	kind of deviation, an index from 1 to 5.
delta	an index from 0 to 3 denoting the degree of departure of the data from the null hypothesis of functional linearity, encoded with 0.
eta	functional parameter employed when type = 4.
composite	flag to indicate the generation of data according to a functional linear model with non-null coefficient (TRUE) or with a null coefficient (FALSE).

Details

The description of the deviations is detailed in the supplementary material of Cuesta-Albertos et al. (2019).

Value

A vector of length length(X.fdata) containing δ Δ(X).

Author(s)

Eduardo García-Portugués ([e-mail]).

References

Cuesta-Albertos, J.A., García-Portugués, E., Febrero-Bande, M. and González-Manteiga, W. (2019). Goodness-of-fit tests for the functional linear model based on randomly projected empirical processes. Annals of Statistics, 47(1):439-467. https://doi.org/10.1214/18-AOS1693

Examples

dev <- list()
k <- 1
mod <- r.cfs.2003(n = 100)
for (i in 1:5) {
  for (delta in 0:3) {
    dev[[k]] <- m.dev(X.fdata = mod$X.fdata, type = i, eta = mod$beta.fdata,
                      delta = delta, composite = TRUE)
    k <- k + 1
  }
}

egarpor/rp.flm.test documentation built on Oct. 20, 2021, 12:31 a.m.