Moreover, it is concluded that used MLE for parameter and LSE for parameter of Pareto distribution for various censoring schemes.
📌 3 Key Takeaways
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Objective & Hypothesis:In this study, bias, mean square error (MSE) and variances of maximum likelihood (ML) and least squares (LS) estimators based on progressive type-II right censored samples for parameters of Pareto distribution are comparised by using Monte Carlo simulation method.
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Key Findings & Data:In this study, bias, mean square error (MSE) and variances of maximum likelihood (ML) and least squares (LS) estimators based on progressive type-II right censored samples for parameters of Pareto distribution are comparised by using Monte Carlo simulation method.
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Conclusion & Impact:Moreover, it is concluded that used MLE for parameter and LSE for parameter of Pareto distribution for various censoring schemes.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:İlerleyen tür sansürleme · en çok olabilirlik (EÇO) tahmin edicisi · en küçük kareler (EKK) tahmin edicisi
Abstract
In this study, bias, mean square error (MSE) and variances of maximum likelihood (ML) and least squares (LS) estimators based on progressive type-II right censored samples for parameters of Pareto distribution are comparised by using Monte Carlo simulation method. Moreover, it is concluded that used MLE for parameter and LSE for parameter of Pareto distribution for various censoring schemes.
Özet
Bu çalışmada, Pareto dağılımının parametrelerinin ilerleyen tür tip-II sağdan sansürlü örneklemlere dayalı en çok olabilirlik (EÇO) ve en küçük kareler (EKK) tahmin edicilerinin yanları, hata kareler ortalamaları ve varyansları Monte Carlo simülasyon çalışması yardımıyla karşılaştırıldı. Ayrıca, değişik sansür şemaları için Pareto dağılımının β parametresi için EÇO tahmin edicisinin kullanılması, λ parametresi için ise EKK tahmin edicisinin kullanılması gerektiği sonucuna ulaşılmıştır
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