rqpd-package: Regression quantiles for panel data (longitudinal data)

In rqpd: Regression Quantiles for Panel Data

Description

The rqpd package provides quantile regression estimation routines and bootstrap inference for panel (longitudinal) data. Currently, the available estimation methods are the penalized fixed-effects model (Koenker, 2004) and a correlated-random-effects type model. (Abrevaya and Dahl, 2008; Bache et al. 2011).

Details

Package:	rqpd
Type:	Package
Version:	0.5
Date:	2011-04-26
License:	GPL >= 2.0
LazyLoad:	yes
LazyData:	yes

Author(s)

Roger Koenker and Stefan Holst Bache

Maintainer: Stefan Holst Bache <[e-mail]>

References

[1] Abrevaya, Jason and Christian M. Dahl. 2008. The effects of birth inputs on birthweight. Journal of Business and Economic Statistics. 26-4. Pages 379–397.

[2] Bache, Stefan Holst; Christian M. Dahl; Johannes Tang Kristensen. 2011. Headlights on tobacco road to low birthweight–Evidence from a battery of quantile regression estimators and a heterogeneous panel.

[3] Koenker, Roger. 2004. Quantile regression for longitudinal data. Journal of Multivariate Analysis. 91-1. Pages 74–89.

Examples

data(bwd)

### A fixed-effects model:

# formula is specified as
fe.form <- dbirwt ~ smoke + dmage + agesq + 
   novisit + pretri2 + pretri3 | as.factor(momid3) 

# estimate the model:
fe.fit <- rqpd(fe.form, panel(lambda=0.5), data=bwd)

### A CRE model:

# formula is specified as
cre.form <- dbirwt ~ smoke + dmage + agesq + 
   novisit + pretri2 + pretri3 | momid3 | smoke + 
   dmage + agesq

# estimate the model:
cre.fit <- rqpd(cre.form, panel(method="cre"), data=bwd)

rqpd documentation built on May 2, 2019, 4:54 p.m.