{"id":596,"date":"2019-01-02T12:26:16","date_gmt":"2019-01-02T12:26:16","guid":{"rendered":"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/?post_type=chapter&#038;p=596"},"modified":"2019-01-03T05:24:06","modified_gmt":"2019-01-03T05:24:06","slug":"nonparametric-bayesian-analysisdirichlet-process-models","status":"publish","type":"chapter","link":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/chapter\/nonparametric-bayesian-analysisdirichlet-process-models\/","title":{"rendered":"Nonparametric Bayesian Analysis: Dirichlet Process Models"},"content":{"raw":"<div><span style=\"float: right\"><a href=\"https:\/\/youtu.be\/vJxWm6Ys-ks\" target=\"_blank\" rel=\"noopener\"><img src=\"http:\/\/epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/2018\/11\/download.png\" alt=\"epgp books\" width=\"75px\" height=\"75px;\" \/><\/a>\r\n<\/span><\/div>\r\n<img class=\"aligncenter size-full wp-image-598\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_006.jpg\" alt=\"\" width=\"1511\" height=\"723\" \/> <img class=\"aligncenter size-full wp-image-599\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_009.jpg\" alt=\"\" width=\"1511\" height=\"737\" \/> <img class=\"aligncenter size-full wp-image-600\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_010.jpg\" alt=\"\" width=\"1510\" height=\"974\" \/> <img class=\"aligncenter size-full wp-image-601\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_011.jpg\" alt=\"\" width=\"1511\" height=\"831\" \/> <img class=\"aligncenter size-full wp-image-602\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_012.jpg\" alt=\"\" width=\"1511\" height=\"811\" \/> <img class=\"aligncenter size-full wp-image-603\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_016.jpg\" alt=\"\" width=\"1509\" height=\"977\" \/> <img class=\"aligncenter size-full wp-image-604\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_019.jpg\" alt=\"\" width=\"1511\" height=\"595\" \/> <img class=\"aligncenter size-full wp-image-605\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_021.jpg\" alt=\"\" width=\"1510\" height=\"732\" \/> <img class=\"aligncenter size-full wp-image-606\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_024.jpg\" alt=\"\" width=\"1510\" height=\"839\" \/> <img class=\"aligncenter size-full wp-image-607\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_026.jpg\" alt=\"\" width=\"1510\" height=\"892\" \/> <img class=\"aligncenter size-full wp-image-608\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_029.jpg\" alt=\"\" width=\"1506\" height=\"795\" \/> <img class=\"aligncenter size-full wp-image-609\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_033.jpg\" alt=\"\" width=\"1511\" height=\"879\" \/> <img class=\"aligncenter size-full wp-image-610\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_034.jpg\" alt=\"\" width=\"1509\" height=\"851\" \/> <img class=\"aligncenter size-full wp-image-611\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_035.jpg\" alt=\"\" width=\"1508\" height=\"798\" \/> <img class=\"aligncenter size-full wp-image-612\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_038.jpg\" alt=\"\" width=\"1507\" height=\"497\" \/> <img class=\"aligncenter size-full wp-image-613\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_042.jpg\" alt=\"\" width=\"1511\" height=\"723\" \/> <img class=\"aligncenter size-full wp-image-614\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_045.jpg\" alt=\"\" width=\"1510\" height=\"687\" \/> <img class=\"aligncenter size-full wp-image-615\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_048.jpg\" alt=\"\" width=\"1504\" height=\"868\" \/> <img class=\"aligncenter size-full wp-image-616\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_051.jpg\" alt=\"\" width=\"1511\" height=\"731\" \/> <img class=\"aligncenter size-full wp-image-617\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_057.jpg\" alt=\"\" width=\"1511\" height=\"1107\" \/> <img class=\"aligncenter size-full wp-image-618\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_062.jpg\" alt=\"\" width=\"1511\" height=\"1017\" \/> <img class=\"aligncenter size-full wp-image-619\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_065.jpg\" alt=\"\" width=\"1509\" height=\"717\" \/> <img class=\"aligncenter size-full wp-image-620\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_070.jpg\" alt=\"\" width=\"1511\" height=\"699\" \/> <img class=\"aligncenter size-full wp-image-621\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_076.jpg\" alt=\"\" width=\"1511\" height=\"857\" \/> <img class=\"aligncenter size-full wp-image-622\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_079.jpg\" alt=\"\" width=\"1511\" height=\"747\" \/> <img class=\"aligncenter size-full wp-image-623\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_081.jpg\" alt=\"\" width=\"1512\" height=\"1102\" \/> <img class=\"aligncenter size-full wp-image-624\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_084.jpg\" alt=\"\" width=\"1509\" height=\"643\" \/> <img class=\"aligncenter size-full wp-image-625\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_087.jpg\" alt=\"\" width=\"1509\" height=\"931\" \/> <img class=\"aligncenter size-full wp-image-626\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_092.jpg\" alt=\"\" width=\"1512\" height=\"1086\" \/> <img class=\"aligncenter size-full wp-image-627\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_097.jpg\" alt=\"\" width=\"1511\" height=\"975\" \/> <img class=\"aligncenter size-full wp-image-628\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_098.jpg\" alt=\"\" width=\"1511\" height=\"1087\" \/> <img class=\"aligncenter size-full wp-image-629\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_101.jpg\" alt=\"\" width=\"1511\" height=\"241\" \/> <img class=\"aligncenter size-full wp-image-630\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_102.jpg\" alt=\"\" width=\"1509\" height=\"941\" \/>\r\n<table style=\"height: 13px\" width=\"730\">\r\n<tbody>\r\n<tr>\r\n<td style=\"width: 657.063px\"><strong>You can view video on Nonparametric Bayesian Analysis: Dirichlet Process Models<\/strong><\/td>\r\n<td style=\"width: 44.0625px\"><a href=\"https:\/\/youtu.be\/vJxWm6Ys-ks\" target=\"_blank\" rel=\"noopener\"><img class=\"alignnone wp-image-120\" src=\"http:\/\/epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/2018\/11\/download.png\" alt=\"\" width=\"36\" height=\"36\" \/><\/a><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n&nbsp;\r\n\r\n<strong>Reference<\/strong>\r\n<ol>\r\n \t<li style=\"text-align: justify\">Beayesian Data Analysis\u201d, 3rd Edition, By Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari and Donald B. Rubin.<\/li>\r\n \t<li style=\"text-align: justify\">Bayesian Statistics: An Introduction\u201d, By Peter Lee, 4th Edition, ISBN: 978-1-118-33257-3.<\/li>\r\n \t<li style=\"text-align: justify\">Monte Carlo Statistical Methods, By Robert, Christian P. andGeorge Casella. 2004. , 2nd edition. Springer.<\/li>\r\n \t<li style=\"text-align: justify\">MCMCpack: Markov Chain Monte Carlo in R.\u201d, (2011), Andrew D. Martin, Kevin M. Quinn, and Jong HeePark,Journal of Statistical Software. 42(9): 1-21.<\/li>\r\n \t<li style=\"text-align: justify\">Applied Bayesian Modeling\u201d By Peter Congdon, 2nd Edition,Wiley,. ISBN: 978-1-119-95151-3<\/li>\r\n \t<li style=\"text-align: justify\">Bayes Linear Statistics, Theory Methods\u201d. By Goldstein,Michael; Woo, David (2007). Wiley. ISBN978-0-470-01562-9.<\/li>\r\n \t<li style=\"text-align: justify\">Hosmer, D.W. and Lemeshow, S. (1989) Applied LogisticRegression. New York: Wiley.<\/li>\r\n \t<li style=\"text-align: justify\">Venables, W. N. and Ripley, B. D. (2002) Modern AppliedStatistics with S. Fourth edition. Springer.<\/li>\r\n \t<li style=\"text-align: justify\">Albert, J. H. and S. Chib. 1993. \\Bayesian Analysis of Binaryand Polychotomous Response Data.\u201dJ. Amer. Statist. Assoc.88, 669-679.<\/li>\r\n \t<li style=\"text-align: justify\">Albert, J. H. and S. Chib. 1995. \\Bayesian Residual Analysisfor Binary Response Regression Models.\u201d Biometrika. 82,747-759.<\/li>\r\n \t<li style=\"text-align: justify\">Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park.2011. \u201cMCMCpack: Markov Chain Monte Carlo in R.\u201d,Journal of Statistical Software. 42(9): 1-21.http:\/\/www.jstatsoft.org\/v42\/i09\/I<\/li>\r\n \t<li style=\"text-align: justify\">Siddhartha Chib. 1995. \\Marginal Likelihood from the GibbsOutput.\u201dJournal of the American Statistical Association.90:1313-1321.<\/li>\r\n \t<li style=\"text-align: justify\">\r\n<div>Peter E. Rossi, Greg M. Allenby and Rob McCulloch, Bayesian Statistics and Marketing (2005), Wiley-Interscience, New York, NY.<\/div><\/li>\r\n \t<li style=\"text-align: justify\">Adelino F. da Silva, cudaBayesreg: Bayesian Computation inCUDA (2010), The R Journal, Vol. 2\/2, 48-55.http:\/\/journal.r-project.org\/archive\/2010-2\/RJournal_2010-2_FerreiradaSilva.pdf<\/li>\r\n \t<li style=\"text-align: justify\">King, Gary, James Honaker, Anne Joseph and KennethScheve. 2001. \\Analyzing incomplete political science data:An alternative algorithm for multiple imputation.\u201dAmericanPolitical Science Review95(1, March):49{69.http:\/\/gking.harvard.edu\/files\/abs\/evil-abs.shtml.<\/li>\r\n \t<li style=\"text-align: justify\">King, Gary, Michael Tomz and Jason Wittenberg. 2000.\\Making the most of statistical analyses: Improvinginterpretation and presentation.\u201dAmerican Journal of PoliticalScience44(2, April):341{355.http:\/\/gking.harvard.edu\/files\/abs\/making-abs.shtml.<\/li>\r\n \t<li style=\"text-align: justify\">Honaker, James, Anne Joseph, Gary King, Kenneth Scheveand Nau- nihal Singh. 1998-2002. \\AMELIA: A program formissing data\u201d.http:\/\/gking.harvard.edu\/amelia.<\/li>\r\n \t<li style=\"text-align: justify\">Honaker, James, Anne Joseph, Gary King, Kenneth Scheveand Nau- nihal Singh. 1998-2002. \\AMELIA: A program formissing data\".http:\/\/gking.harvard.edu\/amelia.<\/li>\r\n \t<li style=\"text-align: justify\">Sethuraman, J. (1994). \\A constructive denition of Dirichletpriors.\"Statistica Sinica, 4:639{650.10<\/li>\r\n \t<li style=\"text-align: justify\">Thomas S. Ferguson. \\A Bayesian Analysis of SomeNonparametric Problems\",Annals of Statistics, 1(2), 1973,209-230.<\/li>\r\n \t<li style=\"text-align: justify\">David Blackwell and James B. MacQueen. \\FergusonDistributions via PolyaUrn Schemes\"Annals of Statistics1(2),1973, 353-355.<\/li>\r\n<\/ol>","rendered":"<div><span style=\"float: right\"><a href=\"https:\/\/youtu.be\/vJxWm6Ys-ks\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"http:\/\/epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/2018\/11\/download.png\" alt=\"epgp books\" width=\"75px\" height=\"75px;\" \/><\/a><br \/>\n<\/span><\/div>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-598\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_006.jpg\" alt=\"\" width=\"1511\" height=\"723\" srcset=\"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_006.jpg 1511w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_006-300x144.jpg 300w, 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srcset=\"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_009.jpg 1511w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_009-300x146.jpg 300w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_009-768x375.jpg 768w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_009-1024x499.jpg 1024w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_009-65x32.jpg 65w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_009-225x110.jpg 225w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_009-350x171.jpg 350w\" sizes=\"auto, (max-width: 1511px) 100vw, 1511px\" \/> <img 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srcset=\"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_097.jpg 1511w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_097-300x194.jpg 300w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_097-768x496.jpg 768w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_097-1024x661.jpg 1024w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_097-65x42.jpg 65w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_097-225x145.jpg 225w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_097-350x226.jpg 350w\" sizes=\"auto, (max-width: 1511px) 100vw, 1511px\" \/> <img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-628\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_098.jpg\" alt=\"\" width=\"1511\" height=\"1087\" srcset=\"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_098.jpg 1511w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_098-300x216.jpg 300w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_098-768x552.jpg 768w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_098-1024x737.jpg 1024w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_098-65x47.jpg 65w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_098-225x162.jpg 225w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_098-350x252.jpg 350w\" sizes=\"auto, (max-width: 1511px) 100vw, 1511px\" \/> <img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-629\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_101.jpg\" alt=\"\" width=\"1511\" height=\"241\" srcset=\"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_101.jpg 1511w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_101-300x48.jpg 300w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_101-768x122.jpg 768w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_101-1024x163.jpg 1024w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_101-65x10.jpg 65w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_101-225x36.jpg 225w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_101-350x56.jpg 350w\" sizes=\"auto, (max-width: 1511px) 100vw, 1511px\" \/> <img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-630\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_102.jpg\" alt=\"\" width=\"1509\" height=\"941\" srcset=\"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_102.jpg 1509w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_102-300x187.jpg 300w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_102-768x479.jpg 768w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_102-1024x639.jpg 1024w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_102-65x41.jpg 65w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_102-225x140.jpg 225w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522661704Bayes_M19_Page_102-350x218.jpg 350w\" sizes=\"auto, (max-width: 1509px) 100vw, 1509px\" \/><\/p>\n<table style=\"height: 13px; width: 730px;\">\n<tbody>\n<tr>\n<td style=\"width: 657.063px\"><strong>You can view video on Nonparametric Bayesian Analysis: Dirichlet Process Models<\/strong><\/td>\n<td style=\"width: 44.0625px\"><a href=\"https:\/\/youtu.be\/vJxWm6Ys-ks\" target=\"_blank\" rel=\"noopener\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-120\" src=\"http:\/\/epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/2018\/11\/download.png\" alt=\"\" width=\"36\" height=\"36\" \/><\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p><strong>Reference<\/strong><\/p>\n<ol>\n<li style=\"text-align: justify\">Beayesian Data Analysis\u201d, 3rd Edition, By Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari and Donald B. Rubin.<\/li>\n<li style=\"text-align: justify\">Bayesian Statistics: An Introduction\u201d, By Peter Lee, 4th Edition, ISBN: 978-1-118-33257-3.<\/li>\n<li style=\"text-align: justify\">Monte Carlo Statistical Methods, By Robert, Christian P. andGeorge Casella. 2004. , 2nd edition. Springer.<\/li>\n<li style=\"text-align: justify\">MCMCpack: Markov Chain Monte Carlo in R.\u201d, (2011), Andrew D. Martin, Kevin M. Quinn, and Jong HeePark,Journal of Statistical Software. 42(9): 1-21.<\/li>\n<li style=\"text-align: justify\">Applied Bayesian Modeling\u201d By Peter Congdon, 2nd Edition,Wiley,. ISBN: 978-1-119-95151-3<\/li>\n<li style=\"text-align: justify\">Bayes Linear Statistics, Theory Methods\u201d. By Goldstein,Michael; Woo, David (2007). Wiley. ISBN978-0-470-01562-9.<\/li>\n<li style=\"text-align: justify\">Hosmer, D.W. and Lemeshow, S. (1989) Applied LogisticRegression. New York: Wiley.<\/li>\n<li style=\"text-align: justify\">Venables, W. N. and Ripley, B. D. (2002) Modern AppliedStatistics with S. Fourth edition. Springer.<\/li>\n<li style=\"text-align: justify\">Albert, J. H. and S. Chib. 1993. \\Bayesian Analysis of Binaryand Polychotomous Response Data.\u201dJ. Amer. Statist. Assoc.88, 669-679.<\/li>\n<li style=\"text-align: justify\">Albert, J. H. and S. Chib. 1995. \\Bayesian Residual Analysisfor Binary Response Regression Models.\u201d Biometrika. 82,747-759.<\/li>\n<li style=\"text-align: justify\">Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park.2011. \u201cMCMCpack: Markov Chain Monte Carlo in R.\u201d,Journal of Statistical Software. 42(9): 1-21.http:\/\/www.jstatsoft.org\/v42\/i09\/I<\/li>\n<li style=\"text-align: justify\">Siddhartha Chib. 1995. \\Marginal Likelihood from the GibbsOutput.\u201dJournal of the American Statistical Association.90:1313-1321.<\/li>\n<li style=\"text-align: justify\">\n<div>Peter E. Rossi, Greg M. 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(1994). \\A constructive denition of Dirichletpriors.&#8221;Statistica Sinica, 4:639{650.10<\/li>\n<li style=\"text-align: justify\">Thomas S. Ferguson. \\A Bayesian Analysis of SomeNonparametric Problems&#8221;,Annals of Statistics, 1(2), 1973,209-230.<\/li>\n<li style=\"text-align: justify\">David Blackwell and James B. MacQueen. \\FergusonDistributions via PolyaUrn Schemes&#8221;Annals of Statistics1(2),1973, 353-355.<\/li>\n<\/ol>\n","protected":false},"author":4,"menu_order":19,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":["dr-sourish-das"],"pb_section_license":""},"chapter-type":[],"contributor":[58],"license":[],"class_list":["post-596","chapter","type-chapter","status-publish","hentry","contributor-dr-sourish-das"],"part":3,"_links":{"self":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters\/596","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/users\/4"}],"version-history":[{"count":5,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters\/596\/revisions"}],"predecessor-version":[{"id":634,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters\/596\/revisions\/634"}],"part":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/parts\/3"}],"metadata":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters\/596\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/media?parent=596"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapter-type?post=596"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/contributor?post=596"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/license?post=596"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}