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

Description Details Author(s) References Examples

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 <[email protected]>

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

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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 31, 2017, 2:36 a.m.