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Extended beta regression in R : shaken, stirred, mixed, and partitioned
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Grun, Bettina, Kosmidis, Ioannis and Zeileis, Achim (2012) Extended beta regression in R : shaken, stirred, mixed, and partitioned. Journal of Statistical Software, 48 (11). pp. 1-25.
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WRAP-extended-beta-regression-R-shaken-stirred-mixed-partitioned-Kosmidis-2012.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution. Download (907Kb) | Preview |
Official URL: https://www.jstatsoft.org/article/view/v048i11
Abstract
Beta regression – an increasingly popular approach for modeling rates and proportions – is extended in various directions: (a) bias correction/reduction of the maximum likelihood estimator, (b) beta regression tree models by means of recursive partitioning, (c) latent class beta regression by means of finite mixture models. All three extensions may be of importance for enhancing the beta regression toolbox in practice to provide more reliable inference and capture both observed and unobserved/latent heterogeneity in the data. Using the analogy of Smithson and Verkuilen (2006), these extensions make beta regression not only “a better lemon squeezer” (compared to classical least squares regression) but a full-fledged modern juicer offering lemon-based drinks: shaken and stirred (bias correction and reduction), mixed (finite mixture model), or partitioned (tree model). All three extensions are provided in the R package betareg (at least 2.4-0), building on generic algorithms and implementations for bias correction/reduction, model-based recursive partioning, and finite mixture models, respectively. Specifically, the new functions betatree() and betamix() reuse the object-oriented flexible implementation from the R packages party and flexmix, respectively.
| Item Type: | Journal Article | ||||||
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| Subjects: | H Social Sciences > HA Statistics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||
| Library of Congress Subject Headings (LCSH): | Regression analysis, R (Computer program language), Recursive partitioning, Mixture distributions (Probability theory), Mathematical statistics | ||||||
| Journal or Publication Title: | Journal of Statistical Software | ||||||
| Publisher: | University of California, Los Angeles | ||||||
| ISSN: | 1548-7660 | ||||||
| Official Date: | 24 May 2012 | ||||||
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| Volume: | 48 | ||||||
| Number: | 11 | ||||||
| Page Range: | pp. 1-25 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| RIOXX Funder/Project Grant: |
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