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Tests of fit for the Laplace distribution based on correcting moments of entropy estimators

机译:基于熵估计量的校正矩的拉普拉斯分布的拟合检验

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In this paper, we first consider the entropy estimators introduced by Vasicek [A test for normality based on sample entropy. J R Statist Soc, Ser B. 1976;38:54-59], Ebrahimi et al. [Two measures of sample entropy. Stat Probab Lett. 1994;20:225-234], Yousefzadeh and Arghami [Testing exponentiality based on type II censored data and a new cdf estimator. Commun Stat - Simul Comput. 2008;37:1479-1499], Alizadeh Noughabi and Arghami [A new estimator of entropy. J Iran Statist Soc. 2010;9:53-64], and Zamanzade and Arghami [Goodness-of-fit test based on correcting moments of modified entropy estimator. J Statist Comput Simul. 2011;81:2077-2093], and the nonparametric distribution functions corresponding to them. We next introduce goodness-of-fit test statistics for the Laplace distribution based on the moments of nonparametric distribution functions of the aforementioned estimators. We obtain power estimates of the proposed test statistics with Monte Carlo simulation and compare them with the competing test statistics against various alternatives. Performance of the proposed new test statistics is illustrated in real cases.
机译:在本文中,我们首先考虑由Vasicek引入的熵估计量[基于样本熵的正态性检验。 J Statist Soc,Ser B. 1976; 38:54-59],Ebrahimi等。 [样本熵的两种度量。 Stat Probab Lett。 1994; 20:225-234],Yousefzadeh和Arghami [基于II型删失数据和新的cdf估计量来测试指数性。通信统计-Simul计算。 2008; 37:1479-1499],Alizadeh Noughabi和Arghami [一种新的熵估算器。伊朗统计家协会。 2010; 9:53-64],以及Zamanzade和Arghami [基于修正熵估计量的校正矩的拟合优度检验。 J Statist Comput Simul。 2011; 81:2077-2093],以及与它们相对应的非参数分布函数。接下来,我们基于上述估计量的非参数分布函数的矩,介绍拉普拉斯分布的拟合优度检验统计量。我们使用蒙特卡洛模拟获得拟议的测试统计量的功效估计,并将其与竞争性测试统计量进行比较,并进行比较。实际情况中说明了所建议的新测试统计数据的性能。

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