dexpectilizeMatR: Dexpectilize a matrix according the a single asymmetric point...

In erfe: Fits Expectile Regression for Panel Fixed Effect Model

Dexpectilize a matrix according the a single asymmetric point τ \in (0, 1).

Description

This function is part of the erfe package. It de-expectilizes a matrix of data vertor-wise, which means subtracting the expectile of level τ \in (0, 1) to every vector of the matrix column-wise. When τ=0.5 then the process of de-expectilizing corresponds to the process of deamining the matrix column-wise. That is, subtracting the mean-column from the column vector.

Usage

dexpectilizeMatR(ymat, aweight, panSizeVec)

Arguments

ymat	Numeric matrix to de-expectilize column-wise.
aweight	Numeric vector of individual asymmetric weight.
panSizeVec	Numeric vector of individual panel size.

Value

Return a de-expectilized matrix of the matrix ymat.

Author(s)

Amadou Barry, [e-mail]

References

Barry, Amadou, Oualkacha, Karim, and Charpentier Arthur. (2022). Weighted asymmetric least squares regression with fixed-effects. arXiv preprint arXiv:2108.04737

Examples

set.seed(13)
temps_obs <- 5
n_subj <- 50
id <- rep(1:n_subj, each=temps_obs) 
asym <- 0.5
panSizeVec <- unname(unlist(lapply(split(id, id), function(x) length(x)))) 
ymat <- matrix(NA, nrow = n_subj * temps_obs, ncol = 5)
ymat <- matrix(mvtnorm::rmvnorm(n_subj * ncol(ymat),
sigma = diag(rep(1, temps_obs))), ncol = ncol(ymat))
aweight <- rep(asym, temps_obs * n_subj)
aweight[!(ymat[, 1] > mean(ymat[, 1]))] = 1 - asym
dexpectilizeMatR(ymat, aweight, panSizeVec)

erfe documentation built on Dec. 16, 2022, 5:15 p.m.