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- W2949641552 abstract "An accurate procedure is proposed to calculate approximate moments of progressive order statistics in the context of statistical inference for lifetime models. The study analyses the performance of power series expansion to approximate the moments for location and scale distributions with high precision and smaller deviations with respect to the exact values. A comparative analysis between exact and approximate methods is shown using some tables and figures. The different approximations are applied in two situations. First, we consider the problem of computing the large sample variance–covariance matrix of maximum likelihood estimators. We also use the approximations to obtain progressively censored sampling plans for log-normal distributed data. These problems illustrate that the presented procedure is highly useful to compute the moments with precision for numerous censoring patterns and, in many cases, is the only valid method because the exact calculation may not be applicable." @default.
- W2949641552 created "2019-06-27" @default.
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- W2949641552 date "2019-06-05" @default.
- W2949641552 modified "2023-09-23" @default.
- W2949641552 title "Accurate computation of single and product moments of order statistics under progressive censoring" @default.
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- W2949641552 doi "https://doi.org/10.1080/00949655.2019.1624749" @default.
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