bic: BIC for the Partially Linear Additive Quantile Regression...

In plaqr: Partially Linear Additive Quantile Regression

Description

Returns the BIC for the partially linear additive quantile regression model from Lee, Noh, and Park (2014).

Usage

bic(fit, ...)

Arguments

fit	a "plaqr" object obtained from a call to plaqr
...	additional parameters which will be ignored

Value

BIC value

Author(s)

Adam Maidman

References

Lee, E. R., Noh, H., and Park, B. U. (2014). Model selection via bayesian information criterion for quantile regression models. Journal of the American Statistical Association 109, 216-229.

Examples

data(simData)

ss <- vector("list", 2)

ss[[2]]$degree <- 3
fit1 <- plaqr(y~., nonlinVars=~z1+z2, data=simData, splinesettings=ss) 

ss[[2]]$degree <- 4
fit2 <- plaqr(y~., nonlinVars=~z1+z2, data=simData, splinesettings=ss) 

ss[[2]]$degree <- 5
fit3 <- plaqr(y~., nonlinVars=~z1+z2, data=simData, splinesettings=ss) 

bic(fit1)
bic(fit2)
bic(fit3)

Example output

Loading required package: quantreg
Loading required package: SparseM

Attaching package: 'SparseM'

The following object is masked from 'package:base':

    backsolve

Loading required package: splines
[1] 3.944204
[1] 3.963902
[1] 3.986438

plaqr documentation built on May 2, 2019, 3:32 p.m.