Publicação
Testing the Validity of Lindley Model Based on Nonparametric Probability Density Functions of Entropy Estimators
| Resumo: | The Lindley distribution is one of the fundamental models applied for reliability models and in the present article, we propose some test statistics for testing the validity of Lindley model based on correcting moments of nonparametric probability density functions of entropy estimators. Critical points and type I error of the tests are obtained and power values of the tests are computed by Monte Carlo simulation. We show that the proposed tests are more powerful than competitor tests. Finally, the proposed tests are illustrated by a real data example. |
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| Autores principais: | Alizadeh Noughabi, Hadi |
| Outros Autores: | Shafaei Noughabi, Mohammad; Alizadeh Noughabi, Hadi |
| Assunto: | Lindley distribution entropy Kullback-Leibler information critical points test power Monte Carlo simulation |
| Ano: | 2026 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | unknown |
| Instituição associada: | Instituto Nacional de Estatística |
| Idioma: | inglês |
| Origem: | REVSTAT-Statistical Journal |
| Resumo: | The Lindley distribution is one of the fundamental models applied for reliability models and in the present article, we propose some test statistics for testing the validity of Lindley model based on correcting moments of nonparametric probability density functions of entropy estimators. Critical points and type I error of the tests are obtained and power values of the tests are computed by Monte Carlo simulation. We show that the proposed tests are more powerful than competitor tests. Finally, the proposed tests are illustrated by a real data example. |
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