{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T07:49:28Z","timestamp":1784706568837,"version":"3.55.0"},"reference-count":26,"publisher":"Oxford University Press (OUP)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,9,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>Standard posterior sampling algorithms, such as Markov chain Monte Carlo procedures, face major challenges in scaling up to massive datasets. We propose a simple and general posterior interval estimation algorithm to rapidly and accurately estimate quantiles of the posterior distributions for one-dimensional functionals. Our algorithm runs Markov chain Monte Carlo in parallel for subsets of the data, and then averages quantiles estimated from each subset. We provide strong theoretical guarantees and show that the credible intervals from our algorithm asymptotically approximate those from the full posterior in the leading parametric order. Our algorithm has a better balance of accuracy and efficiency than its competitors across a variety of simulations and a real-data example.<\/jats:p>","DOI":"10.1093\/biomet\/asx033","type":"journal-article","created":{"date-parts":[[2017,5,18]],"date-time":"2017-05-18T11:11:58Z","timestamp":1495105918000},"page":"665-680","source":"Crossref","is-referenced-by-count":32,"title":["Simple, scalable and accurate posterior interval estimation"],"prefix":"10.1093","volume":"104","author":[{"given":"Cheng","family":"Li","sequence":"first","affiliation":[{"name":"Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, Singapore stalic@nus.edu.sg"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanvesh","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Department of Statistics and Actuarial Science, The University of Iowa, 241 Schaeffer Hall, 20 East Washington Street, Iowa City, Iowa 52242, U.S.A. sanvesh-srivastava@uiowa.edu"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David B.","family":"Dunson","sequence":"additional","affiliation":[{"name":"Department of Statistical Science, Duke University, Box 90251, Durham, North Carolina 27708, U.S.A. dunson@duke.edu"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2017,6,25]]},"reference":[{"key":"2019071815501483800_B1","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1002\/jae.851","article-title":"Estimating the effect of smoking on birth outcomes using a matched panel data approach.","volume":"21","author":"Abrevaya","year":"2006","journal-title":"J. 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