aiccrq: Akaike's Information Criterion for weighted quantile...

In WRTDStidal: Weighted Regression for Water Quality Evaluation in Tidal Waters

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)

WRTDStidal documentation built on Oct. 20, 2023, 5:08 p.m.