{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T04:31:41Z","timestamp":1791520301744,"version":"4.3.4"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2019,12,17]],"date-time":"2019-12-17T00:00:00Z","timestamp":1576540800000},"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":[[2020,2,1]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>For many applications with multivariate data, random-field models capturing departures from Gaussianity within realizations are appropriate. For this reason, we formulate a new class of multivariate non-Gaussian models based on systems of stochastic partial differential equations with additive type G noise whose marginal covariance functions are of Mat\u00e9rn type. We consider four increasingly flexible constructions of the noise, where the first two are similar to existing copula-based models. In contrast with these, the last two constructions can model non-Gaussian spatial data without replicates. Computationally efficient methods for likelihood-based parameter estimation and probabilistic prediction are proposed, and the flexibility of the models suggested is illustrated by numerical examples and two statistical applications.<\/jats:p>","DOI":"10.1111\/rssb.12351","type":"journal-article","created":{"date-parts":[[2019,12,17]],"date-time":"2019-12-17T14:53:10Z","timestamp":1576594390000},"page":"215-239","source":"Crossref","is-referenced-by-count":33,"title":["Multivariate Type G Mat\u00e9rn Stochastic Partial Differential Equation Random Fields"],"prefix":"10.1093","volume":"82","author":[{"given":"David","family":"Bolin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonas","family":"Wallin","sequence":"additional","affiliation":[{"name":"Lund University \u00a0 Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2019,12,17]]},"reference":[{"key":"2023022408362976600_","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1137\/S0363012902417267","article-title":"Stability of stochastic approximation under verifiable conditions","volume":"44","author":"Andrieu","year":"2005","journal-title":"SIAM J. 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