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Semiparametric Bayesian Inference for Mean-Covariance Regression Models
In this paper, we propose a Bayesian semiparametric mean-covariance regression model with known covariance structures. A mixture model is used to describe the potential non-normal distribution of the regression errors. Moreover, an empirical likelihood adjusted mixture of Dirichlet process model is...
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| Published in: | Acta mathematica Sinica. English series 2017-06, Vol.33 (6), p.748-760 |
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| Main Authors: | , , , |
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| container_end_page | 760 |
| container_issue | 6 |
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| container_title | Acta mathematica Sinica. English series |
| container_volume | 33 |
| creator | Yu, Han Jun Shen, Jun Shan Li, Zhao Nan Fang, Xiang Zhong |
| description | In this paper, we propose a Bayesian semiparametric mean-covariance regression model with known covariance structures. A mixture model is used to describe the potential non-normal distribution of the regression errors. Moreover, an empirical likelihood adjusted mixture of Dirichlet process model is constructed to produce distributions with given mean and variance constraints. We illustrate through simulation studies that the proposed method provides better estimations in some non-normal cases. We also demonstrate the implementation of our method by analyzing the data set from a sleep deprivation study. |
| doi_str_mv | 10.1007/s10114-016-6357-7 |
| format | article |
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We also demonstrate the implementation of our method by analyzing the data set from a sleep deprivation study.</description><subject>Bayesian analysis</subject><subject>Computer simulation</subject><subject>Constraint modelling</subject><subject>Covariance</subject><subject>Dirichlet</subject><subject>Dirichlet problem</subject><subject>Empirical analysis</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Nonparametric statistics</subject><subject>Normal distribution</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Sleep</subject><subject>Sleep deprivation</subject><subject>Statistical inference</subject><subject>半参数</subject><subject>协方差结构</subject><subject>回归模型</subject><subject>回归误差</subject><subject>均值</subject><subject>贝叶斯推断</subject><subject>非正态分布</subject><issn>1439-8516</issn><issn>1439-7617</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNp9UE1LAzEQDaJgrf4Ab4ueo5nsZpMctWgttAh-nEOaTuqWdtMmrdB_b8oW8SQMvGHmfcAj5BrYHTAm7xMwgIoyqGldCknlCelBVWoqa5Cnx10JqM_JRUoLxoTQrO6R4TuumrWNdoXb2Lji0e4xNbYtRq3HiK3DwodYTNC2dBC-bcy_fHvDecSUmtAWkzDDZbokZ94uE14dsU8-n58-Bi90_DocDR7G1HEttlRm4MoLx-3Uc2dBOVnOUHrGFNMzV0kAZyWvtNY4myr0rJIaeGmdziPKPrntfNcxbHaYtmYRdrHNkQaU1ooroVRmQcdyMaQU0Zt1bFY27g0wc-jLdH2Z3Jc59GVk1vBOkzK3nWP84_yP6OYY9BXa-SbrfpNqyYFpxkX5Ay3peKE</recordid><startdate>20170601</startdate><enddate>20170601</enddate><creator>Yu, Han Jun</creator><creator>Shen, Jun Shan</creator><creator>Li, Zhao Nan</creator><creator>Fang, Xiang Zhong</creator><general>Institute of Mathematics, Chinese Academy of Sciences and Chinese Mathematical Society</general><general>Springer Nature B.V</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>~WA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7TB</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>KR7</scope><scope>L.-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M2O</scope><scope>M2P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>20170601</creationdate><title>Semiparametric Bayesian Inference for Mean-Covariance Regression Models</title><author>Yu, Han Jun ; 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| subjects | Bayesian analysis Computer simulation Constraint modelling Covariance Dirichlet Dirichlet problem Empirical analysis Mathematics Mathematics and Statistics Nonparametric statistics Normal distribution Regression analysis Regression models Sleep Sleep deprivation Statistical inference 半参数 协方差结构 回归模型 回归误差 均值 贝叶斯推断 非正态分布 |
| title | Semiparametric Bayesian Inference for Mean-Covariance Regression Models |
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