Journal article 752 views

Multivariate quantile function models

Yuzhi Cai

Statistica Sinica, Volume: 20, Issue: 2, Pages: 481 - 496

Swansea University Author:

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Abstract

Multivariate quantiles have been defined by a number of researchers and can be estimated by different methods. However, little work can be found in the literature about Bayesian estimation of joint quantiles of multivariate random variables. In this paper we present a multivariate quantile function...

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Published in: Statistica Sinica 1017-0405 Taipei 2010 https://cronfa.swan.ac.uk/Record/cronfa6997 No Tags, Be the first to tag this record!
first_indexed 2013-07-23T11:57:00Z 2018-02-09T04:34:42Z cronfa6997 SURis 2016-05-01T15:24:34.8984188v269972012-01-31Multivariate quantile function modelseff7b8626ab4cc6428eef52516fda7d60000-0003-3509-9787YuzhiCaiYuzhi Caitruefalse2012-01-31BAFMultivariate quantiles have been defined by a number of researchers and can be estimated by different methods. However, little work can be found in the literature about Bayesian estimation of joint quantiles of multivariate random variables. In this paper we present a multivariate quantile function model and propose a Bayesian method to estimate the model parameters. The methodology developed here enables us to estimate the multivariate quantile surfaces and the joint probability without direct use of the joint probability distribution or density functions of the random variables of interest. Furthermore, simulation studies and applications of the methodology to bivariate economics data sets show that the method works well both theoretically and practically.Journal ArticleStatistica Sinica202481496Taipei1017-0405Bayesian method, τth quantile surface, τth quantile curve,311220102010-12-31http://www3.stat.sinica.edu.tw/statistica/j20n2/J20N21/J20N21.htmlCOLLEGE NANMEAccounting and FinanceCOLLEGE CODEBAFSwansea University2016-05-01T15:24:34.89841882012-01-31T11:05:25.6830000School of ManagementAccounting and FinanceYuzhiCai0000-0003-3509-97871 2016-05-01T15:24:34.8984188 v2 6997 2012-01-31 Multivariate quantile function models eff7b8626ab4cc6428eef52516fda7d6 0000-0003-3509-9787 Yuzhi Cai Yuzhi Cai true false 2012-01-31 BAF Multivariate quantiles have been defined by a number of researchers and can be estimated by different methods. However, little work can be found in the literature about Bayesian estimation of joint quantiles of multivariate random variables. In this paper we present a multivariate quantile function model and propose a Bayesian method to estimate the model parameters. The methodology developed here enables us to estimate the multivariate quantile surfaces and the joint probability without direct use of the joint probability distribution or density functions of the random variables of interest. Furthermore, simulation studies and applications of the methodology to bivariate economics data sets show that the method works well both theoretically and practically. Journal Article Statistica Sinica 20 2 481 496 Taipei 1017-0405 Bayesian method, τth quantile surface, τth quantile curve, 31 12 2010 2010-12-31 http://www3.stat.sinica.edu.tw/statistica/j20n2/J20N21/J20N21.html COLLEGE NANME Accounting and Finance COLLEGE CODE BAF Swansea University 2016-05-01T15:24:34.8984188 2012-01-31T11:05:25.6830000 School of Management Accounting and Finance Yuzhi Cai 0000-0003-3509-9787 1 Multivariate quantile function models Multivariate quantile function models Yuzhi Cai Multivariate quantile function models Multivariate quantile function models Multivariate quantile function models Multivariate quantile function models Multivariate quantile function models eff7b8626ab4cc6428eef52516fda7d6 eff7b8626ab4cc6428eef52516fda7d6_***_Yuzhi Cai Yuzhi Cai Yuzhi Cai Journal article Statistica Sinica 20 2 481 2010 Swansea University 1017-0405 Taipei School of Management schoolofmanagement School of Management schoolofmanagement School of Management Accounting and Finance{{{_:::_}}}School of Management{{{_:::_}}}Accounting and Finance http://www3.stat.sinica.edu.tw/statistica/j20n2/J20N21/J20N21.html 0 0 Multivariate quantiles have been defined by a number of researchers and can be estimated by different methods. However, little work can be found in the literature about Bayesian estimation of joint quantiles of multivariate random variables. In this paper we present a multivariate quantile function model and propose a Bayesian method to estimate the model parameters. The methodology developed here enables us to estimate the multivariate quantile surfaces and the joint probability without direct use of the joint probability distribution or density functions of the random variables of interest. Furthermore, simulation studies and applications of the methodology to bivariate economics data sets show that the method works well both theoretically and practically. 2010-12-31T03:17:11Z 1737024268207652864 10.887993