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检索条件"主题词=MCECM algorithm"
8 条 记 录,以下是1-10 订阅
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Hidden Markov Latent Variable Models with Multivariate Longitudinal Data
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BIOMETRICS 2017年 第1期73卷 313-323页
作者: Song, Xinyuan Xia, Yemao Zhu, Hongtu Chinese Univ Hong Kong Dept Stat Shenzhen Res Inst Shatin Hong Kong Peoples R China Nanjing Forestry Univ Dept Appl Math Nanjing Jiangsu Peoples R China Univ North Carolina Chapel Hill Dept Biostat Chapel Hill NC USA
Cocaine addiction is chronic and persistent, and has become a major social and health problem in many countries. Existing studies have shown that cocaine addicts often undergo episodic periods of addiction to, moderat... 详细信息
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Multivariate generalized hyperbolic laws for modeling financial log-returns: Empirical and theoretical considerations
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APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY 2020年 第5期36卷 757-775页
作者: Fotopoulos, Stergios B. Paparas, Alex Jandhyala, Venkata K. Washington State Univ Dept Finance & Management Sci Pullman WA 99164 USA Washington State Univ Dept Math & Stat Pullman WA 99164 USA
The aim of this study is to consider the multivariate generalized hyperbolic (MGH) distribution for modeling financial log-returns. Beginning with the multivariate geometric subordinated Brownian motion for asset pric... 详细信息
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Application of EM-type algorithms to spatial data
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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 1997年 第3期26卷 669-683页
作者: Alonso, FJ Angulo, JM Bueso, MC UNIV GRANADA DEPT ESTAD & IOE-18071 GRANADASPAIN
We consider the problem of maximum-likelihood estimation and smoothing for lattice processes using incomplete data. In a previous paper (Alonso et al., 1996) the authors developed a methodology based on an application... 详细信息
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Elliptical regression models for multivariate sample-selection bias correction
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JOURNAL OF THE KOREAN STATISTICAL SOCIETY 2016年 第3期45卷 422-438页
作者: Kim, Hea-Jung Kim, Hyoung-Moon Dongguk Univ Seoul Dept Stat Seoul South Korea Konkuk Univ Dept Appl Stat Seoul South Korea
In linear regression, a multivariate sample-selection scheme often applies to the dependent variable, which results in missing observations on the variable. This induces the sample selection bias, i.e. a standard regr... 详细信息
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Maximum likelihood estimation of nonlinear structural equation models
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PSYCHOMETRIKA 2002年 第2期67卷 189-210页
作者: Lee, SY Zhu, HT Chinese Univ Hong Kong Dept Stat Shatin Hong Kong Peoples R China Univ Victoria Dept Math & Stat Victoria BC V8W 2Y2 Canada
The existing maximum likelihood theory and its computer software in structural equation modeling are established based on linear relationships among manifest variables and latent variables. However, models with nonlin... 详细信息
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Segmented classification analysis with a class of rectangle-screened elliptical populations
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JOURNAL OF APPLIED STATISTICS 2015年 第9期42卷 1877-1895页
作者: Kim, Hea-Jung Dongguk Univ Seoul Dept Stat Seoul 100715 South Korea
In many practical situations, a statistical practitioner often faces a problem of classifying an object from one of the segmented (or screened) populations where the segmentation was conducted by a set of screening va... 详细信息
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Robust statistical modelling using the multivariate skew t distribution with complete and incomplete data
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STATISTICAL MODELLING 2011年 第3期11卷 253-277页
作者: Lin, Tsung-I Lin, Tzy-Chy Natl Chung Hsing Univ Dept Appl Math Taichung 40227 Taiwan Natl Chung Hsing Univ Inst Stat Taichung 40227 Taiwan Ctr Drug Evaluat Div Clin Sci Taipei Taiwan
Missing data is inevitable in many situations that could hamper data analysis for scientific investigations. We establish flexible analytical tools for multivariate skew t models when fat-tailed, asymmetric and missin... 详细信息
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Generalized linear latent models for multivariate longitudinal measurements mixed with hidden Markov models
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JOURNAL OF MULTIVARIATE ANALYSIS 2016年 152卷 259-275页
作者: Xia, Ye-Mao Tang, Nian-Sheng Gou, Jian-Wei Nanjing Forestry Univ Dept Appl Math Nanjing 210037 Jiangsu Peoples R China Yunnan Univ Dept Stat Kunming 650091 Peoples R China
This article presents a generalized linear latent variable model for analyzing multivariate longitudinal data within the hidden Markov model framework. The relationships among multiple items are captured by several co... 详细信息
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