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Estimation of Distribution Function Based on Presmoothed Relative-Risk Function

Estimation of Distribution Function Based on Presmoothed Relative-Risk Function
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摘要 In this article, the lifetime data subjecting to right random censoring is considered. Nonparametric estimation of the distribution function based on the conception of presmoothed estimation of relative-risk function and the properties of the estimator by using methods of numerical modeling are discussed. In the model under consideration, the estimates were compared using numerical methods to determine which of the estimates is actually better. In this article, the lifetime data subjecting to right random censoring is considered. Nonparametric estimation of the distribution function based on the conception of presmoothed estimation of relative-risk function and the properties of the estimator by using methods of numerical modeling are discussed. In the model under consideration, the estimates were compared using numerical methods to determine which of the estimates is actually better.
作者 Abdurakhim Akhmedovich Abdushukurov Sukhrob Bakhodirovich Bozorov Dilshod Ravilovich Mansurov Abdurakhim Akhmedovich Abdushukurov;Sukhrob Bakhodirovich Bozorov;Dilshod Ravilovich Mansurov(Moscow State University Tashkent Branch, Tashkent, Uzbekistan;Guliston State University, Gulistan, Uzbekistan;Navoi State Pedagogical Institute, Navoi, Uzbekistan)
出处 《Applied Mathematics》 2022年第2期191-204,共14页 应用数学(英文)
关键词 Random Censorship Product-Limit Relative Risk Presmoothed Proportional Hazards Asymptotic Representation Strong Consistency Asymptotic Normality Random Censorship Product-Limit Relative Risk Presmoothed Proportional Hazards Asymptotic Representation Strong Consistency Asymptotic Normality
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