aiccrq {WRTDStidal} | R Documentation |
Akaike's Information Criterion for weighted quantile regression
Description
Get AIC values for a single weighted quantile regression as used in WRTDS models
Usage
aiccrq(mod_in, tau = 0.5)
Arguments
mod_in |
input crq model |
tau |
numeric indicating quantile to evaluate |
Details
The AIC value is based on the log-likelihood estimate of the model that accounts for the specific quantile, the minimum of the objective function (rho), and the number of model parameters. The residuals are specific to the WRTDS model such that this function cannot be applied to arbitrary crq models.
Value
AIC estimate
Examples
# get wts for a model centered on the first observation
ref_in <- tidobj[1, ]
ref_wts <- getwts(tidobj, ref_in)
# get the model
mod <- quantreg::crq(
survival::Surv(res, not_cens, type = "left") ~
dec_time + flo + sin(2*pi*dec_time) + cos(2*pi*dec_time),
weights = ref_wts,
data = tidobj,
method = "Portnoy"
)
aiccrq(mod)
[Package WRTDStidal version 1.1.4 Index]