沙漠
发表于 2025-3-23 11:19:53
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FLACK
发表于 2025-3-23 17:57:14
Bestehende Erfolgsgrundlagen schwinden, arising from economics, medicine and engineering. After discussing the issues of sampling bias due to double-truncation, we briefly review likelihood-based inference methods for doubly truncated data. We finally compare double-truncation with interval/right censoring.
罗盘
发表于 2025-3-23 18:04:19
Peter Bleses,Britta Busse,Andreas FriemerSEF). We introduce specific models in the SEF, and computational algorithms for maximum likelihood estimators (MLEs) under these models. We review the asymptotic theory for the MLE and then give the standard error and confidence interval. We also introduce an R package “double.truncation” (Emura et
担忧
发表于 2025-3-23 23:13:55
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Fresco
发表于 2025-3-24 05:04:55
Peter Bleses,Britta Busse,Andreas Friemeretric approaches, no specific distributional assumptions are made, and it is described how the estimator originally derived in Efron and Petrosian (J Am Stat Assoc 94(447):824–834, 1999) is defined and motivated. It turns out that the solution to the estimation problem can be regarded as a fixed-poi
Capitulate
发表于 2025-3-24 07:48:31
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GONG
发表于 2025-3-24 11:46:10
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相互影响
发表于 2025-3-24 15:04:13
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易怒
发表于 2025-3-24 22:28:04
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Palpitation
发表于 2025-3-24 23:24:47
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