000129423 001__ 129423 000129423 005__ 20240711085513.0 000129423 0247_ $$2doi$$a10.1007/s11749-023-00895-6 000129423 0248_ $$2sideral$$a135633 000129423 037__ $$aART-2024-135633 000129423 041__ $$aeng 000129423 100__ $$0(orcid)0000-0003-3859-0248$$aCastillo-Mateo, Jorge$$uUniversidad de Zaragoza 000129423 245__ $$aBayesian joint quantile autoregression 000129423 260__ $$c2024 000129423 5060_ $$aAccess copy available to the general public$$fUnrestricted 000129423 5203_ $$aQuantile regression continues to increase in usage, providing a useful alternative to customary mean regression. Primary implementation takes the form of so-called multiple quantile regression, creating a separate regression for each quantile of interest. However, recently, advances have been made in joint quantile regression, supplying a quantile function which avoids crossing of the regression across quantiles. Here, we turn to quantile autoregression (QAR), offering a fully Bayesian version. We extend the initial quantile regression work of Koenker and Xiao (J Am Stat Assoc 101(475):980–990, 2006. https://doi.org/10.1198/016214506000000672) in the spirit of Tokdar and Kadane (Bayesian Anal 7(1):51–72, 2012. https://doi.org/10.1214/12-BA702). We offer a directly interpretable parametric model specification for QAR. Further, we offer a pth-order QAR(p) version, a multivariate QAR(1) version, and a spatial QAR(1) version. We illustrate with simulation as well as a temperature dataset collected in Aragón, Spain. 000129423 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E46-20R$$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-116873GB-I00$$9info:eu-repo/grantAgreement/EUR/MICINN/TED2021-130702B-I00 000129423 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000129423 592__ $$a0.773$$b2023 000129423 593__ $$aStatistics, Probability and Uncertainty$$c2023$$dQ2 000129423 593__ $$aStatistics and Probability$$c2023$$dQ2 000129423 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000129423 700__ $$aGelfand, Alan E. 000129423 700__ $$0(orcid)0000-0002-0174-789X$$aAsín, Jesús$$uUniversidad de Zaragoza 000129423 700__ $$0(orcid)0000-0002-9052-9674$$aCebrián, Ana C.$$uUniversidad de Zaragoza 000129423 700__ $$0(orcid)0000-0002-7974-7435$$aAbaurrea, Jesús 000129423 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera. 000129423 773__ $$g33 (2024), 335–357$$pTest (Madrid)$$tTest$$x1133-0686 000129423 8564_ $$s998539$$uhttps://zaguan.unizar.es/record/129423/files/texto_completo.pdf$$yVersión publicada 000129423 8564_ $$s1137058$$uhttps://zaguan.unizar.es/record/129423/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000129423 909CO $$ooai:zaguan.unizar.es:129423$$particulos$$pdriver 000129423 951__ $$a2024-07-11-08:52:31 000129423 980__ $$aARTICLE