JDS Journal of Data Science 1683-8602 1680-743X 1680-743X School of Statistics, Renmin University of China JDS1003 10.6339/21-JDS1003 Statistical Data Science Validation of Stepwise-Based Procedure in GAMLSS RamiresThiago G.thiagogentil@gmail.com1∗ https://orcid.org/0000-0002-7312-2717 NakamuraLuiz R.2 RighettoAna J.3 PescimRodrigo R.4 MazucheliJosmar5 RigbyRobert A.6 StasinopoulosDimitrios M.6 Universidade Tecnológica Federal do Paraná, Apucarana, Brazil Universidade Federal de Santa Catarina, Florianópolis, Brazil Alvaz Agritech, Londrina, Brazil Universidade Estadual de Londrina, Londrina, Brazil Universidade Estadual de Maringá, Maringá, Brazil London Metropolitan University, London, United Kingdom Corresponding author Email: thiagogentil@gmail.com. 20211022021 19196110 Supplementary Material

Please note that the following supplementary files are available online: i) suppl_stepgaic.pdf: p-values for the selected variables in each simulated scenario; and ii) codes_stepgaic.zip: all codes in R software that were used to conduct the simulation studies presented in this paper.

 112020 12021 2021 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.2021 Open access article under the CC BY license.

One of the key features in regression models consists in selecting appropriate characteristics that explain the behavior of the response variable, in which stepwise-based procedures occupy a prominent position. In this paper we performed several simulation studies to investigate whether a specific stepwise-based approach, namely Strategy A, properly selects authentic variables into the generalized additive models for location, scale and shape framework, considering Gaussian, zero inflated Poisson and Weibull distributions. Continuous (with linear and nonlinear relationships) and categorical explanatory variables are considered and they are selected through some goodness-of-fit statistics. Overall, we conclude that the Strategy A greatly performed.

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