| dexpectilizeMatR {erfe} | R Documentation |
Dexpectilize a matrix according the a single asymmetric point
\tau \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 \tau \in (0, 1) to every vector of
the matrix column-wise. When \tau=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, barryhafia@gmail.com
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)