{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T02:53:46Z","timestamp":1782442426855,"version":"3.54.5"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T00:00:00Z","timestamp":1687478400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>We propose a methodology for modelling and comparing probability distributions within a Bayesian nonparametric framework. Building on dependent normalised random measures, we consider a prior distribution for a collection of discrete random measures where each measure is a linear combination of a set of latent measures, interpretable as characteristic traits shared by different distributions, with positive random weights. The model is nonidentified and a method for postprocessing posterior samples to achieve identified inference is developed. This uses Riemannian optimisation to solve a nontrivial optimisation problem over a Lie group of matrices. The effectiveness of our approach is validated on simulated data and in two applications to two real-world data sets: school student test scores and personal incomes in California. Our approach leads to interesting insights for populations and easily interpretable posterior inference.<\/jats:p>","DOI":"10.1093\/jrsssb\/qkad062","type":"journal-article","created":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T15:16:55Z","timestamp":1685546215000},"page":"1247-1270","source":"Crossref","is-referenced-by-count":3,"title":["Normalised latent measure factor models"],"prefix":"10.1093","volume":"85","author":[{"given":"Mario","family":"Beraha","sequence":"first","affiliation":[{"name":"Department of Economics and Statistics, University of Torino , Torino , Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jim E","family":"Griffin","sequence":"additional","affiliation":[{"name":"Department of Statistical Science, University College London , London , 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