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检索条件"主题词=Generalized Linear Models"
1428 条 记 录,以下是31-40 订阅
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Asymptotic Properties of the Maximum Likelihood Estimate in generalized linear models with Stochastic Regressors
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Acta Mathematica Sinica,English Series 2006年 第6期22卷 1679-1686页
作者: Jie Li DING Xi Ru CHEN School of Mathematics and Statistics Wuhan University Wuhan 430072 P. R. China Graduate School Chinese Academy of Sciences Beijing 100039 P. R. China
For generalized linear models (GLM), in case the regressors are stochastic and have different distributions, the asymptotic properties of the maximum likelihood estimate (MLE) β^n of the parameters are studied. U... 详细信息
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Modelling and mapping spatio-temporal trends of heavy metal accumulation in moss and natural surface soil monitored 1990-2010 throughout Norway by multivariate generalized linear models and geostatistics
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ATMOSPHERIC ENVIRONMENT 2014年 99卷 85-93页
作者: Nickel, Stefan Hertel, Anne Pesch, Roland Schroeder, Winfried Steinnes, Eiliv Uggerud, Hilde Thelle Univ Vechta D-49377 Vechta Germany Norwegian Univ Sci & Technol Dept Chem NO-7491 Trondheim Norway Norwegian Inst Air Res NILU N-2027 Kjeller Norway
Objective. This study explores the statistical relations between the accumulation of heavy metals in moss and natural surface soil and potential influencing factors such as atmospheric deposition by use of multivariat... 详细信息
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Fuzzy clusterwise quasi-likelihood generalized linear models
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ADVANCES IN DATA ANALYSIS AND CLASSIFICATION 2010年 第4期4卷 255-270页
作者: Hwang, Heungsun Tomiuk, Marc A. McGill Univ Dept Psychol Montreal PQ H3A 1B1 Canada HEC Montreal Dept Mkt Montreal PQ H3T 2A7 Canada
The quasi-likelihood method has emerged as a useful approach to the parameter estimation of generalized linear models (GLM) in circumstances where there is insufficient distributional information to construct a likeli... 详细信息
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Optimal Combination of linear and Spectral Estimators for generalized linear models
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FOUNDATIONS OF COMPUTATIONAL MATHEMATICS 2022年 第5期22卷 1513-1566页
作者: Mondelli, Marco Thrampoulidis, Christos Venkataramanan, Ramji IST Austria Campus 1 A-3400 Klosterneuburg Austria Univ British Columbia Dept Elect & Comp Engn 5500-2332 Main Mall Vancouver BC V6T 1Z4 Canada Univ Cambridge Dept Engn Trumpington St Cambridge CB2 1PZ England
We study the problem of recovering an unknownsignal x givenmeasurements obtained from a generalized linear model with a Gaussian sensing matrix. Two popular solutions are based on a linear estimator (x) over cap (L) a... 详细信息
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CORRECTION FOR COVARIATE MEASUREMENT ERROR IN generalized linear-models - A BOOTSTRAP APPROACH
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BIOMETRICS 1995年 第3期51卷 1127-1132页
作者: HAUKKA, JK National Public Health Institute Helsinki Finland.
A two-phase bootstrap method is proposed for correcting covariate measurement error. Two data sets are needed: validation data for approximating the measurement model and data with a response variable. Bootstrap sampl... 详细信息
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Bayesian model comparison in generalized linear models across multiple groups
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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2002年 第3期39卷 311-327页
作者: Liao, TFT Univ Essex Dept Sociol Wivenhoe Pk CO4 3SQ Essex England Univ Illinois Sch Sociol & Stat Urbana IL 61801 USA
This paper extends the statistical method known as generalized linear Bayesian modeling developed by Adrian Raftery to the comparison of generalized linear models across multiple groups. The extension considers all re... 详细信息
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On power and sample size calculations for likelihood ratio tests in generalized linear models
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BIOMETRICS 2000年 第4期56卷 1192-1196页
作者: Shieh, G Natl Chiao Tung Univ Dept Management Sci Hsinchu 30050 Taiwan
A direct extension of the approach described in Self, Mauritsen, and Ohara (1992, Biometrics 48, 31-39) for power and sample size calculations in generalized linear models is presented. The major feature of the propos... 详细信息
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l1 regularized multiplicative iterative path algorithm for non-negative generalized linear models
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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2016年 101卷 289-299页
作者: Mandal, B. N. Ma, Jun ICAR Indian Agr Stat Res Inst New Delhi 110012 India Macquarie Univ Dept Stat N Ryde NSW 2109 Australia
In regression modeling, often a restriction that regression coefficients are non-negative is faced. The problem of model selection in non-negative generalized linear models (NNGLM) is considered using lasso, where reg... 详细信息
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Penalized likelihood regression for generalized linear models with non-quadratic penalties
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ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS 2011年 第3期63卷 585-615页
作者: Antoniadis, Anestis Gijbels, Irene Nikolova, Mila Univ Grenoble 1 Dept Stat Lab Jean Kuntzmann Tour IRMA F-38041 Grenoble 9 France Katholieke Univ Leuven Dept Math Leuven Stat Res Ctr LStat B-3001 Leuven Belgium PRES UniverSud CNRS ENS Cachan Ctr Math & Leurs Applicat F-94235 Cachan France
One of the popular method for fitting a regression function is regularization: minimizing an objective function which enforces a roughness penalty in addition to coherence with the data. This is the case when formulat... 详细信息
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Instrumental variable approach to covariate measurement error in generalized linear models
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ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS 2012年 第3期64卷 475-493页
作者: Abarin, Taraneh Wang, Liqun Univ Manitoba Dept Stat Winnipeg MB R3T 2N2 Canada
The paper presents the method of moments estimation for generalized linear measurement error models using the instrumental variable approach. The measurement error has a parametric distribution that is not necessarily... 详细信息
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