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Many examples are sketched, including missing value situations, applications to grouped, censored or truncated data, finite mixture models, variance component estimation, hyperparameter estimation, iteratively reweighted least squares and factor analysis.<\/jats:p>","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","type":"journal-article","created":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T01:38:07Z","timestamp":1544146687000},"page":"1-22","source":"Crossref","is-referenced-by-count":34440,"title":["Maximum Likelihood from Incomplete Data Via the\n                    <i>EM<\/i>\n                    Algorithm"],"prefix":"10.1093","volume":"39","author":[{"given":"A. P.","family":"Dempster","sequence":"first","affiliation":[{"name":"Harvard University and Educational Testing Service"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"N. 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