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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Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_03036898_v_n_p_Boente |
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todo:paper_03036898_v_n_p_Boente2023-10-03T15:19:43Z Goodness-of-fit test for directional data Boente, G. Rodriguez, D. Manteiga, W.G. Asymptotic properties Bootstrap tests Density estimation Hypothesis testing Maximum likelihood estimators Spherical data Von Mises distribution 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. Fil:Boente, G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Rodriguez, D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. INPR English info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03036898_v_n_p_Boente |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-134 |
collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
language |
English |
orig_language_str_mv |
English |
topic |
Asymptotic properties Bootstrap tests Density estimation Hypothesis testing Maximum likelihood estimators Spherical data Von Mises distribution |
spellingShingle |
Asymptotic properties Bootstrap tests Density estimation Hypothesis testing Maximum likelihood estimators Spherical data Von Mises distribution Boente, G. Rodriguez, D. Manteiga, W.G. Goodness-of-fit test for directional data |
topic_facet |
Asymptotic properties Bootstrap tests Density estimation Hypothesis testing Maximum likelihood estimators Spherical data Von Mises distribution |
description |
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. |
format |
INPR |
author |
Boente, G. Rodriguez, D. Manteiga, W.G. |
author_facet |
Boente, G. Rodriguez, D. Manteiga, W.G. |
author_sort |
Boente, G. |
title |
Goodness-of-fit test for directional data |
title_short |
Goodness-of-fit test for directional data |
title_full |
Goodness-of-fit test for directional data |
title_fullStr |
Goodness-of-fit test for directional data |
title_full_unstemmed |
Goodness-of-fit test for directional data |
title_sort |
goodness-of-fit test for directional data |
url |
http://hdl.handle.net/20.500.12110/paper_03036898_v_n_p_Boente |
work_keys_str_mv |
AT boenteg goodnessoffittestfordirectionaldata AT rodriguezd goodnessoffittestfordirectionaldata AT manteigawg goodnessoffittestfordirectionaldata |
_version_ |
1807317496414339072 |