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Goodness‐of‐fit Test for Directional Data
Authors:Graciela Boente  Daniela Rodriguez  Wenceslao González Manteiga
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
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.
Keywords:asymptotic properties  bootstrap tests  density estimation  hypothesis testing  maximum likelihood estimators  spherical data  von Mises distribution
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