{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,20]],"date-time":"2026-09-20T12:07:12Z","timestamp":1789906032585,"version":"4.0.1"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"vor","delay-in-days":7640,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["DA-01-0433"],"award-info":[{"award-number":["DA-01-0433"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DMS-95-10511"],"award-info":[{"award-number":["DMS-95-10511"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2002,5,1]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>We obtain the residual information criterion RIC, a selection criterion based on the residual log-likelihood, for regression models including classical regression models, Box\u2013Cox transformation models, weighted regression models and regression models with autoregressive moving average errors. We show that RIC is a consistent criterion, and that simulation studies for each of the four models indicate that RIC provides better model order choices than the Akaike information criterion, corrected Akaike information criterion, final prediction error, Cp and Radj2, except when the sample size is small and the signal-to-noise ratio is weak. In this case, none of the criteria performs well. Monte Carlo results also show that RIC is superior to the consistent Bayesian information criterion BIC when the signal-to-noise ratio is not weak, and it is comparable with BIC when the signal-to-noise ratio is weak and the sample size is large.<\/jats:p>","DOI":"10.1111\/1467-9868.00335","type":"journal-article","created":{"date-parts":[[2003,5,6]],"date-time":"2003-05-06T15:13:15Z","timestamp":1052233995000},"page":"237-252","source":"Crossref","is-referenced-by-count":85,"title":["Regression Model Selection\u2014A Residual Likelihood Approach"],"prefix":"10.1093","volume":"64","author":[{"given":"Peide","family":"Shi","sequence":"first","affiliation":[{"name":"Peking University , Beijing , People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chih-Ling","family":"Tsai","sequence":"additional","affiliation":[{"name":"University of California at Davis , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2002,6,20]]},"reference":[{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/BF02506337","article-title":"Statistical predictor identification","volume":"22","author":"Akaike","year":"1970","journal-title":"Ann. Inst. Statist. Math."},{"key":"2023040200504880600_","first-page":"267","volume-title":"Proc. 2nd Int. Symp. Information Theory","author":"Petrov","year":"1973"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1080\/01621459.1981.10477649","article-title":"An analysis of transformation revisited","volume":"76","author":"Bickel","year":"1981","journal-title":"J. Am. Statist. Ass."},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1111\/j.2517-6161.1964.tb00553.x","article-title":"An analysis of transformations (with discussion)","volume":"26","author":"Box","year":"1964","journal-title":"J. R. Statist. Soc."},{"key":"2023040200504880600_","volume-title":"Applied Mixed Models in Medicine","author":"Brown","year":"1999"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-2917-7","volume-title":"Model Selection and Inference (a Practical Information-theoretic Approach)","author":"Burnham","year":"1998"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4899-2873-3","volume-title":"Transformation and Weighting in Regression","author":"Carroll","year":"1988"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","DOI":"10.1002\/9780470316764","volume-title":"Sensitivity Analysis in Linear Regression","author":"Chatterjee","year":"1988"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1080\/01621459.2000.10474318","article-title":"Bias reduction of autoregressive estimates in time series regression model through restricted maximum likelihood","volume":"95","author":"Cheang","year":"2000","journal-title":"J. Am. Statist. Ass."},{"key":"2023040200504880600_","first-page":"625","article-title":"A note on the estimation of parameters of the autoregressive-moving average process","volume":"64","author":"Cooper","year":"1977","journal-title":"Biometrika"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"31","DOI":"10.2307\/1267913","article-title":"Restricted maximum likelihood (REML) estimation of variance components in the mixed model","volume":"18","author":"Corbeil","year":"1976","journal-title":"Technometrics"},{"key":"2023040200504880600_","volume-title":"Analysis of Longitudinal Data","author":"Diggle","year":"1994"},{"key":"2023040200504880600_","first-page":"49","article-title":"Maximum likelihood estimation of regression models with auto-regressive-moving average disturbances","volume":"66","author":"Harvey","year":"1979","journal-title":"Biometrika"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1093\/biomet\/61.2.383","article-title":"Bayesian inference for variance components using only error contrasts","volume":"61","author":"Harville","year":"1974","journal-title":"Biometrika"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1093\/biomet\/84.2.474","article-title":"Linear regression after spline transformation","volume":"84","author":"He","year":"1997","journal-title":"Biometrika"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1111\/1467-9868.00125","article-title":"Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion","volume":"60","author":"Hurvich","year":"1998","journal-title":"J. R. Statist. Soc."},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1093\/biomet\/76.2.297","article-title":"Regression and time series model selection in small samples","volume":"76","author":"Hurvich","year":"1989","journal-title":"Biometrika"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4899-4489-4","volume-title":"Longitudinal Data with Serial Correlation: a State-space Approach","author":"Jones","year":"1993"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/0304-4076(81)90119-6","article-title":"Joint estimation and testing for functional form and heteroscedasticity","volume":"15","author":"Lahiri","year":"1981","journal-title":"J. Econometr."},{"key":"2023040200504880600_","volume-title":"Model Selection","author":"Linhart","year":"1986"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"337","DOI":"10.2307\/2988471","article-title":"A comparison of tests for heteroscedasticity","volume":"45","author":"Lyon","year":"1996","journal-title":"Statistician"},{"key":"2023040200504880600_","first-page":"661","article-title":"Some comments on Cp","volume":"15","author":"Mallows","year":"1973","journal-title":"Technometrics"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4899-3242-6","author":"McCullagh","year":"1989","journal-title":"Generalized Linear Models"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","DOI":"10.1002\/0471722073","volume-title":"Generalized, Linear, and Mixed Models","author":"McCulloch","year":"2000"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1093\/biomet\/58.3.545","article-title":"Recovery of inter-block information when block sizes are unequal","volume":"8","author":"Patterson","year":"1971","journal-title":"Biometrika"},{"key":"2023040200504880600_","volume-title":"Estimation of Variance Components and Applications","author":"Rao","year":"1988"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","article-title":"Estimating the dimension of a model","volume":"6","author":"Schwarz","year":"1978","journal-title":"Ann. Statist."},{"key":"2023040200504880600_","volume-title":"Regression Analysis\u2014Theory, Methods, and Applications","author":"Sen","year":"1990"},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1080\/10618600.1999.10474799","article-title":"Semiparametric and additive model selection using an improved Akaike information criterion","volume":"58","author":"Simonoff","year":"1999","journal-title":"J. Comput. Graph. Statist."},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1080\/01621459.1984.10477073","article-title":"Regression models with time series errors","volume":"79","author":"Tsay","year":"1984","journal-title":"J. Am. Statist. Ass."},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1111\/j.2517-6161.1989.tb01745.x","article-title":"On the use of marginal likelihood in time series model estimation","volume":"51","author":"Tunnicliffe Wilson","year":"1989","journal-title":"J. R. Statist. Soc."},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1111\/j.1467-842X.1990.tb01015.x","article-title":"A conditional derivation of residual maximum likelihood","volume":"32","author":"Verbyla","year":"1990","journal-title":"Aust. J. Statist."},{"key":"2023040200504880600_","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1111\/j.2517-6161.1993.tb01918.x","article-title":"Modelling variance heterogeneity: residual maximum likelihood and diagnostics","volume":"55","year":"1993","journal-title":"J. R. Statist. Soc."}],"container-title":["Journal of the Royal Statistical Society Series B: Statistical Methodology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1111%2F1467-9868.00335","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1111%2F1467-9868.00335","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/academic.oup.com\/jrsssb\/article-pdf\/64\/2\/237\/49721511\/jrsssb_64_2_237.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jrsssb\/article-pdf\/64\/2\/237\/49721511\/jrsssb_64_2_237.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T17:47:58Z","timestamp":1733766478000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jrsssb\/article\/64\/2\/237\/7098404"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2002,5,1]]},"references-count":33,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2002,6,20]]},"published-print":{"date-parts":[[2002,5,1]]}},"URL":"https:\/\/doi.org\/10.1111\/1467-9868.00335","relation":{},"ISSN":["1369-7412","1467-9868"],"issn-type":[{"value":"1369-7412","type":"print"},{"value":"1467-9868","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2002,5]]},"published":{"date-parts":[[2002,5,1]]}}}