{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T18:09:42Z","timestamp":1649182182291},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2019,9,16]],"date-time":"2019-09-16T00:00:00Z","timestamp":1568592000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,12,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>We develop and implement a novel M-estimation method for locally stationary diffusions observed at discrete time-points. We give sufficient conditions for the local stationarity of general time-inhomogeneous diffusions. Then we focus on locally stationary diffusions with time-varying parameters, for which we define our M-estimators and derive their limit theory.<\/jats:p>","DOI":"10.1093\/biomet\/asz042","type":"journal-article","created":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T15:17:10Z","timestamp":1563376630000},"page":"941-956","source":"Crossref","is-referenced-by-count":0,"title":["Semiparametric segment M-estimation for locally stationary diffusions"],"prefix":"10.1093","volume":"106","author":[{"given":"P -Y","family":"Del\u00e9amont","sequence":"first","affiliation":[{"name":"Research Center for Statistics, University of Geneva, Blv. Pont d\u2019Arve 40, 1211 Geneva, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D La","family":"Vecchia","sequence":"additional","affiliation":[{"name":"Research Center for Statistics, University of Geneva, Blv. 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