Testing parametric models in linear-directional regression

Garcia Portugues, Eduardo;Van Keilegom, Ingrid;Crujeiras and, Rosa M.;Gonzalez-Manteiga, Wenceslao
(2016) Scandinavian Journal of Statistics : theory and applications — Vol. 43, n° 4, p. 1178-1191 (2016)

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Authors
  • Garcia Portugues, Eduardo
    Author
  • Van Keilegom, IngridUCLouvain
    Author
  • Crujeiras and, Rosa M.
    Author
  • Gonzalez-Manteiga, WenceslaoUCLouvain
    Author
Abstract
This paper presents a goodness-of-fit test for parametric regression models with scalar response and directional predictor, that is, a vector on a sphere of arbitrary dimension. The testing procedure is based on the weighted squared distance between a smooth and a parametric regression estimator, where the smooth regression estimator is obtained by a projected local approach. Asymptotic behaviour of the test statistic under the null hypothesis and local alternatives is provided, jointly with a consistent bootstrap algorithm for application in practice. A simulation study illustrates the performance of the test in finite samples. The procedure is applied to test a linear model in text mining.
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Garcia Portugues, E., Van Keilegom, I., Crujeiras and, R. M., & Gonzalez-Manteiga, W. (2016). Testing parametric models in linear-directional regression. Scandinavian Journal of Statistics : theory and applications, 43(4), 1178-1191. https://doi.org/10.1111/sjos.12236 (Original work published 2016)