具有面板计数数据的反向均值模型的非参数推理

IF 1.5 2区数学 Q2 STATISTICS & PROBABILITY

Bernoulli Pub Date : 2022-11-01 DOI:10.3150/21-bej1444

Li Liu, Wen Su, G. Yin, Xingqiu Zhao, Ying Zhang

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引用次数: 3

摘要

李立1温素2郭生义2应章3和邢秋4武汉大学数学与统计学院，湖北武汉，430072，中国电子邮箱：lliu.math@whu.edu.cn2香港香港大学统计及精算学系电子邮箱：jenna.wen.su@connect.hku.hk电子邮件：gyin@hku.hk；通讯作者3美国内布拉斯加州奥马哈内布拉斯加大学医学中心生物统计学系电子邮件：ying.zhang@unmc.edu4香港香港理工大学应用数学系电子邮箱：xingqiu.zhao@polyu.edu.hk

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Nonparametric inference for reversed mean models with panel count data

LI LIU1 WEN SU2 GUOSHENG YIN2 YING ZHANG3 and XINGQIU ZHAO4 1School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, 430072, China E-mail: lliu.math@whu.edu.cn 2Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong E-mail: jenna.wen.su@connect.hku.hk E-mail: gyin@hku.hk; Corresponding author 3Department of Biostatistics, University of Nebraska Medical Center, Omaha, NE, USA E-mail: ying.zhang@unmc.edu 4Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong E-mail: xingqiu.zhao@polyu.edu.hk

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来源期刊

Bernoulli 数学-统计学与概率论

CiteScore

3.40

自引率

0.00%

发文量

116

审稿时长

6-12 weeks

期刊介绍： BERNOULLI is the journal of the Bernoulli Society for Mathematical Statistics and Probability, issued four times per year. The journal provides a comprehensive account of important developments in the fields of statistics and probability, offering an international forum for both theoretical and applied work. BERNOULLI will publish: Papers containing original and significant research contributions: with background, mathematical derivation and discussion of the results in suitable detail and, where appropriate, with discussion of interesting applications in relation to the methodology proposed. Papers of the following two types will also be considered for publication, provided they are judged to enhance the dissemination of research: Review papers which provide an integrated critical survey of some area of probability and statistics and discuss important recent developments. Scholarly written papers on some historical significant aspect of statistics and probability.