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Entropy Estimation Using Bootstrap and Jackknife Methods and its Application in Testing Normality
Atefe Pourkazemi , Hadi Alizadeh Noughabi , Sara Jomhoori
Abstract:   (1152 Views)
In this paper, the Bootstrap and Jackknife methods are stated and using these methods, entropy is estimated. Then the estimators based on Bootstrap and Jackknife are investigated in terms of bias and RMSE using simulation. The proposed estimators are compared with other entropy estimators by Monte Carlo simulation. Results show that the entropy estimators based on Bootstrap and Jackknife have a good performance as compared to the other estimators. Next, some tests of normality based on the proposed estimators are introduced and the power of these tests are compared with other tests.
Keywords: Entropy, Bootstrap, Jackknife, Testing Normality, Test Power
Full-Text [PDF 7100 kb]   (154 Downloads)    
Type of Study: Research | Subject: Statistical Inference
Received: 2017/09/19 | Accepted: 2018/08/11
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مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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