Goodness‐of‐fit Test for Directional Data |
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Authors: | Graciela Boente Daniela Rodriguez Wenceslao González Manteiga |
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Affiliation: | 1. Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and CONICET;2. Departamento de Estadística e Investigación Operativa, Universidad de Santiago de Compostela |
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Abstract: | 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. |
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Keywords: | asymptotic properties bootstrap tests density estimation hypothesis testing maximum likelihood estimators spherical data von Mises distribution |
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