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检索条件"主题词=Generalized Linear Models"
1429 条 记 录,以下是61-70 订阅
排序:
Goodness-of-fit testing in high dimensional generalized linear models
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JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY 2020年 第3期82卷 773-795页
作者: Jankova, Jana Shah, Rajen D. Buhlmann, Peter Samworth, Richard J. Univ Cambridge Cambridge England Eidgenoss Tech Hsch Zurich Zurich Switzerland
We propose a family of tests to assess the goodness of fit of a high dimensional generalized linear model. Our framework is flexible and may be used to construct an omnibus test or directed against testing specific no... 详细信息
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The existence of maximum likelihood estimate in high-dimensional binary response generalized linear models
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ELECTRONIC JOURNAL OF STATISTICS 2020年 第2期14卷 4028-4053页
作者: Tang, Wenpin Ye, Yuting Columbia Univ Dept Ind Engn & Operat Res New York NY 10027 USA Univ Calif Berkeley Div Biostat Berkeley CA USA
Motivated by recent works on the high-dimensional logistic regression, we establish that the existence of the maximum likelihood estimate exhibits a phase transition for a wide range of generalized linear models with ... 详细信息
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Communication-efficient distributed estimator for generalized linear models with a diverging number of covariates
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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2021年 157卷 107154-107154页
作者: Zhou, Ping Yu, Zhen Ma, Jingyi Tian, Maozai Fan, Ye Beijing Informat Sci & Technol Univ Sch Appl Sci Beijing Peoples R China Renmin Univ China Sch Stat Beijing Peoples R China Cent Univ Finance & Econ Sch Stat & Math Beijing Peoples R China
Nowadays, it has become increasingly common to store large-scale data sets distributedly across a great number of clients. The aim of the study is to develop a distributed estimator for generalized linear models (GLMs... 详细信息
来源: 评论
Tuning-free ridge estimators for high-dimensional generalized linear models
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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2021年 159卷 107205-107205页
作者: Huang, Shih-Ting Xie, Fang Lederer, Johannes Ruhr Univ Bochum Dept Math D-44801 Bochum Germany
Ridge estimators regularize the squared Euclidean lengths of parameters. Such estimators are mathematically and computationally attractive but involve tuning parameters that need to be calibrated. It is shown that rid... 详细信息
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ClusterBootstrap: An R package for the analysis of hierarchical data using generalized linear models with the cluster bootstrap
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BEHAVIOR RESEARCH METHODS 2020年 第2期52卷 572-590页
作者: Deen, Mathijs de Rooij, Mark Leiden Univ Inst Psychol Methodol & Stat Unit Wassenaarsewegm 52 NL-2333 AK Leiden Netherlands
In the analysis of clustered or hierarchical data, a variety of statistical techniques can be applied. Most of these techniques have assumptions that are crucial to the validity of their outcome. Mixed models rely on ... 详细信息
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Landscape Complexity for the Empirical Risk of generalized linear models  1
Landscape Complexity for the Empirical Risk of Generalized L...
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1st Mathematical and Scientific Machine Learning Conference, MSML 2020
作者: Maillard, Antoine Arous, Gérard Ben Biroli, Giulio Laboratoire de Physique de l'Ecole Normale Supérieure ENS Université PSL CNRS Sorbonne Université Université Paris-Diderot Sorbonne Paris Cité Paris France Courant Institute of Mathematical Sciences New York University 251 Mercer Street New YorkNY10012 United States
We present a method to obtain the average and the typical value of the number of critical points of the empirical risk landscape for generalized linear estimation problems and variants. This represents a substantial e... 详细信息
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Restricted ridge estimator in generalized linear models: Monte Carlo simulation studies on Poisson and binomial distributed responses
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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2019年 第4期48卷 1191-1218页
作者: Kurtoglu, Fikriye Ozkale, M. Revan Cukurova Univ Dept Stat Fac Sci & Letters TR-01330 Adana Turkey
It is known that collinearity among the explanatory variables in generalized linear models (GLMs) inflates the variance of maximum likelihood estimators. To overcome multicollinearity in GLMs, ordinary ridge estimator... 详细信息
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Bayesian model selection for generalized linear models using non-local priors
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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2019年 133卷 285-296页
作者: Shi, Guiling Lim, Chae Young Maiti, Tapabrata Michigan State Univ Dept Stat & Probabil E Lansing MI 48824 USA Seoul Natl Univ Dept Stat Seoul South Korea
Variable selection is currently an important research topic under both frequentist and Bayesian framework. While most developments in Bayesian model selection literature are based on a local prior on regression parame... 详细信息
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Overlapping group lasso for high-dimensional generalized linear models
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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2019年 第19期48卷 4903-4917页
作者: Zhou, Shengbin Zhou, Jingke Zhang, Bo Harbin Normal Univ Dept Stat Harbin Heilongjiang Peoples R China Lingnan Normal Univ Sch Informat Engn 29 Cunjin Rd Zhanjiang Guangdong Peoples R China
Structured sparsity has recently been a very popular technique to deal with the high-dimensional data. In this paper, we mainly focus on the theoretical problems for the overlapping group structure of generalized line... 详细信息
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Maximum likelihood estimation of generalized linear models for adaptive designs: Applications and asymptotics
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BIOMETRICAL JOURNAL 2019年 第3期61卷 630-651页
作者: Selvaratnam, Selvakkadunko Yi, Yanqing Oyet, Alwell Univ Alberta Dept Math & Stat Sci Edmonton AB Canada Mem Univ Dept Community Hlth & Humanities St John NF Canada Mem Univ Dept Math & Stat St John NF ALC 5S7 Canada
Due to increasing discoveries of biomarkers and observed diversity among patients, there is growing interest in personalized medicine for the purpose of increasing the well-being of patients (ethics) and extending hum... 详细信息
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