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PoweR: A Reproducible Research Tool to Ease Monte Carlo Power Simulation Studies for Goodness-of-fit Tests in R

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  • Lafaye de Micheaux, Pierre
  • Tran, Viet Anh

Abstract

The PoweR package aims to help obtain or verify empirical power studies for goodnessof-fit tests for independent and identically distributed data. The current version of our package is only valid for simple null hypotheses or for pivotal test statistics for which the set of critical values does not depend on a particular choice of a null distribution (and on nuisance parameters) under the non-simple null case. We also assume that the distribution of the test statistic is continuous. As a reproducible research computational tool it can be viewed as helping to simply reproducing (or detecting errors in) simulation results already published in the literature. Using our package helps also in designing new simulation studies. The empirical levels and powers for many statistical test statistics under a wide variety of alternative distributions can be obtained quickly and accurately using a C/C++ and R environment. The parallel package can be used to parallelize computations when a multicore processor is available. The results can be displayed using LATEX tables or specialized graphs, which can be directly incorporated into a report. This article gives an overview of the main design aims and principles of our package, as well as strategies for adaptation and extension. Hands-on illustrations are presented to help new users in getting started.

Suggested Citation

  • Lafaye de Micheaux, Pierre & Tran, Viet Anh, 2016. "PoweR: A Reproducible Research Tool to Ease Monte Carlo Power Simulation Studies for Goodness-of-fit Tests in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i03).
  • Handle: RePEc:jss:jstsof:v:069:i03
    DOI: http://hdl.handle.net/10.18637/jss.v069.i03
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    References listed on IDEAS

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    1. Editors, 2004. "Cumulative index, volumes 1-4," Stata Journal, StataCorp LP, vol. 4(4), pages 492-498, December.
    2. מחקר - ביטוח לאומי, 2004. "Annual Survey 2002-2003," Working Papers 21, National Insurance Institute of Israel.
    3. -, 2004. "Economic survey of the Caribbean, 2003-2004," Sede Subregional de la CEPAL para el Caribe (Estudios e Investigaciones) 27562, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
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    Cited by:

    1. Qiang Xia & Zhiqiang Zhang & Wai Keung Li, 2020. "A Portmanteau Test for Smooth Transition Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 722-730, September.
    2. Lorentz Jäntschi & Sorana D. Bolboacă, 2018. "Computation of Probability Associated with Anderson–Darling Statistic," Mathematics, MDPI, vol. 6(6), pages 1-17, May.
    3. González-Estrada, Elizabeth & Villaseñor, José A., 2016. "A ratio goodness-of-fit test for the Laplace distribution," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 30-35.

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