Validation of Stepwise-Based Procedure in GAMLSS

Ramires, Thiago G.; Nakamura, Luiz R.; Righetto, Ana J.; Pescim, Rodrigo R.; Mazucheli, Josmar; Rigby, Robert A.; Stasinopoulos, Dimitrios M.

doi:10.6339/21-JDS1003

Journal of Data Science

Validation of Stepwise-Based Procedure in GAMLSS

Volume 19, Issue 1 (2021), pp. 96–110

Thiago G. Ramires Luiz R. Nakamura

Ana J. Righetto All authors (7)

https://doi.org/10.6339/21-JDS1003

Pub. online: 10 February 2021 Type: Statistical Data Science

Received
1 November 2020

Accepted
1 January 2021

Published
10 February 2021

Abstract

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.

Supplementary material

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.

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backward forward model selection smoothing

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