In this paper, we study the problem of testing the hypothesis on whether the density f of a random variable on a sphere belongs to a given parametric class of densities. We propose two test statistics based on the L2 and L1 distances between a non-parametric density estimator adapted to circular data and a smoothed version of the specified density. The asymptotic distribution of the L2 test statistic is provided under the null hypothesis and contiguous alternatives. We also consider a bootstrap method to approximate the distribution of both test statistics. Through a simulation study, we explore the moderate sample performance of the proposed tests under the null hypothesis and under different alternatives. Finally, the procedure is illustrated by analysing a real data set based on wind direction measurements. © 2013 Board of the Foundation of the Scandinavian Journal of Statistics.
Documento: | Artículo |
Título: | Goodness-of-fit test for directional data |
Autor: | Boente, G.; Rodriguez, D.; Manteiga, W.G. |
Filiación: | Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires and CONICET Departamento de Estadística e Investigación Operativa Universidad de Santiago de Compostela |
Idioma: | Inglés |
Palabras clave: | Asymptotic properties; Bootstrap tests; Density estimation; Hypothesis testing; Maximum likelihood estimators; Spherical data; Von Mises distribution |
Año: | 2013 |
DOI: | http://dx.doi.org/10.1111/sjos.12020 |
Título revista: | Scandinavian Journal of Statistics |
Título revista abreviado: | Scand. J. Stat. |
ISSN: | 03036898 |
Registro: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03036898_v_n_p_Boente |