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政大機構典藏 > 商學院 > 統計學系 > 期刊論文 > Item 140.119/148693

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/148693

Title:	Bias approximations for likelihood‐based estimators
Authors:	翁久幸 Weng, Ruby Chiu-Hsing;Coad, D. Stephen
Contributors:	統計系
Keywords:	bias calculation;l2penalized likelihood;maximum likelihood estimation;stopping time;very weak approximation;Woodroofe–Stein identity
Date:	2021-12
Issue Date:	2023-12-13 13:54:59 (UTC+8)
Abstract:	Bias approximation has played an important rôle in statistical inference, and numerous bias calculation techniques have been proposed under different contexts. We provide a unified approach to approximating the bias of the maximum likelihood estimator and the l2 penalized likelihood estimator for both linear and nonlinear models, where the design variables are allowed to be random and the sample size can be a stopping time. The proposed method is based on the Woodroofe–Stein identity and is justified by very weak approximations. The accuracy of the derived bias formulas is assessed by simulation for several examples. The bias of the ridge estimator in high-dimensional settings is also discussed.
Relation:	Scandinavian Journal of Statistics, Vol.48, No.4, pp.1474-1497
Data Type:	article
DOI 連結:	https://doi.org/10.1111/sjos.12499
DOI:	10.1111/sjos.12499
Appears in Collections:	[統計學系] 期刊論文

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