Goodness-of-fit test for directional data
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 dat...
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| Autores principales: | , , |
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| Formato: | INPR |
| Lenguaje: | English |
| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_03036898_v_n_p_Boente |
| Aporte de: |
| Sumario: | 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. |
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