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Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned

  • Bettina Grün

    ()

  • Ioannis Kosmidis

    ()

  • Achim Zeileis

    ()

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.

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File URL: http://eeecon.uibk.ac.at/wopec2/repec/inn/wpaper/2011-22.pdf
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Paper provided by Faculty of Economics and Statistics, University of Innsbruck in its series Working Papers with number 2011-22.

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Length: 31
Date of creation: Oct 2011
Date of revision:
Handle: RePEc:inn:wpaper:2011-22
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  1. Achim Zeileis & Yves Croissant, . "Extended Model Formulas in R: Multiple Parts and Multiple Responses," Journal of Statistical Software, American Statistical Association, vol. 34(i01).
  2. Ospina, Raydonal & Cribari-Neto, Francisco & Vasconcellos, Klaus L.P., 2006. "Improved point and interval estimation for a beta regression model," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 960-981, November.
  3. Achim Zeileis & Kurt Hornik, 2007. "Generalized M-fluctuation tests for parameter instability," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 61(4), pages 488-508.
  4. Achim Zeileis & Friedrich Leisch & Kurt Hornik & Christian Kleiber, . "strucchange: An R Package for Testing for Structural Change in Linear Regression Models," Journal of Statistical Software, American Statistical Association, vol. 7(i02).
  5. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
  6. Bettina Grün & Friedrich Leisch, . "FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters," Journal of Statistical Software, American Statistical Association, vol. 28(i04).
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