global_rq {GET} | R Documentation |
Global quantile regression
Description
Global tests of significance for the effect of covariates in quantile regression
Usage
global_rq(
nsim,
formula.full,
formula.reduced,
taus,
data,
contrasts = NULL,
permutationstrategy = c("Freedman-Lane", "Freedman-Lane+remove zeros",
"within nuisance", "remove location", "remove location scale", "remove quantile"),
savefuns = FALSE,
rq.args = NULL,
lm.args = NULL,
GET.args = NULL,
mc.cores = 1L,
mc.args = NULL,
cl = NULL
)
Arguments
nsim |
The number of random permutations. |
formula.full |
The formula specifying the general linear model,
see |
formula.reduced |
The formula of the reduced model with nuisance factors only. This model should be nested within the full model. |
taus |
The quantiles to be used. |
data |
data.frame where to look for variables. |
contrasts |
Passed directly to |
permutationstrategy |
The permutation strategy to be used. See details. |
savefuns |
Logical. If TRUE, then the functions from permutations are saved to the attribute simfuns. |
rq.args |
Additional arguments passed to |
lm.args |
A named list of additional arguments to be passed to |
GET.args |
A named list of additional arguments to be passed to |
mc.cores |
The number of cores to use, i.e. at most how many child processes will be run simultaneously.
Must be at least one, and parallelization requires at least two cores. On a Windows computer mc.cores must be 1
(no parallelization). For details, see |
mc.args |
A named list of additional arguments to be passed to |
cl |
Allows parallelization through the use of |
Details
The possible permutation strategies include "Freedman-Lane" (FL), "Freedman-Lane+remove zeros" (FL+), "within nuisance" (WN), "remove location" (RL), "remove location scale" (RLS), "remove quantile" (RQ), which correspond to those in Mrkvička et al. (Section 4.1-4.6 and Table 1).
Value
A global_envelope
or combined_global_envelope
object,
which can be printed and plotted directly.
References
Mrkvička, T., Konstantinou, K., Kuronen, M. and Myllymäki, M. (2023) Global quantile regression. arXiv:2309.04746 [stat.ME]. https://doi.org/10.48550/arXiv.2309.04746
Myllymäki, M and Mrkvička, T. (2023). GET: Global envelopes in R. arXiv:1911.06583 [stat.ME]. https://doi.org/10.48550/arXiv.1911.06583
Freedman, D., & Lane, D. (1983) A nonstochastic interpretation of reported significance levels. Journal of Business & Economic Statistics, 1(4), 292-298. doi:10.2307/1391660
Examples
if(require("quantreg", quietly=TRUE)) {
data("stackloss")
res <- global_rq(nsim = 19, # Increase nsim for serious analysis!
formula.full = stack.loss ~ Air.Flow + Water.Temp + Acid.Conc.,
formula.reduced = stack.loss ~ Water.Temp,
taus = seq(0.1, 0.9, length=10), permutationstrategy = "remove quantile",
data = stackloss, GET.args = list(typeone = "fwer"))
plot(res)
}