Wyszynski, K;
Marra, G;
(2017)
Sample selection models for count data in R.
Computational Statistics
10.1007/s00180-017-0762-y.
(In press).
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Abstract
We provide a detailed hands-on tutorial for the R package SemiParSampleSel (version 1.5). The package implements selection models for count responses fitted by penalized maximum likelihood estimation. The approach can deal with non-random sample selection, flexible covariate effects, heterogeneous selection mechanisms and varying distributional parameters. We provide an overview of the theoretical background and then demonstrate how SemiParSampleSel can be used to fit interpretable models of different complexity. We use data from the German Socio-Economic Panel survey (SOEP v28, 2012. doi: 10.5684/soep.v28) throughout the tutorial.
| Type: | Article |
|---|---|
| Title: | Sample selection models for count data in R |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s00180-017-0762-y |
| Publisher version: | https://doi.org/10.1007/s00180-017-0762-y |
| Language: | English |
| Additional information: | © The Author(s) 2017. This article is an open access publication and is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Copula, Non-random sample selection, Penalized regression spline, Selection bias Count response, Tutorial |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10041776 |
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