112406 20240319080958.0 doi 10.1007/s13253-022-00493-3 sideral 128501 ART-2022-128501 eng Castillo-Mateo, Jorge Universidad de Zaragoza (orcid)0000-0003-3859-0248 Spatial Modeling of Day-Within-Year Temperature Time Series: An Examination of Daily Maximum Temperatures in Aragon, Spain 2022 Access copy available to the general public Unrestricted Acknowledging a considerable literature on modeling daily temperature data, we propose a multi-level spatiotemporal model which introduces several innovations in order to explain the daily maximum temperature in the summer period over 60 years in a region containing Aragon, Spain. The model operates over continuous space but adopts two discrete temporal scales, year and day within year. It captures temporal dependence through autoregression on days within year and also on years. Spatial dependence is captured through spatial process modeling of intercepts, slope coefficients, variances, and autocorrelations. The model is expressed in a form which separates fixed effects from random effects and also separates space, years, and days for each type of effect. Motivated by exploratory data analysis, fixed effects to capture the influence of elevation, seasonality, and a linear trend are employed. Pure errors are introduced for years, for locations within years, and for locations at days within years. The performance of the model is checked using a leave-one-out cross-validation. Applications of the model are presented including prediction of the daily temperature series at unobserved or partially observed sites and inference to investigate climate change comparison. Supplementary materials accompanying this paper appear online. info:eu-repo/grantAgreement/ES/DGA/E46-20R info:eu-repo/grantAgreement/ES/MCED/FPU-1505266 info:eu-repo/grantAgreement/ES/MICINN/PID2020-116873GB-I00 info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 1.4 2022 STATISTICS & PROBABILITY 64 / 125 = 0.512 2022 Q3 T2 MATHEMATICAL & COMPUTATIONAL BIOLOGY 44 / 55 = 0.8 2022 Q4 T3 BIOLOGY 72 / 92 = 0.783 2022 Q4 T3 0.711 2022 Agricultural and Biological Sciences (miscellaneous) 2022 Q1 Statistics, Probability and Uncertainty 2022 Q2 Statistics and Probability 2022 Q2 Applied Mathematics 2022 Q2 Environmental Science (miscellaneous) 2022 Q2 3.2 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Lafuente, Miguel Universidad de Zaragoza (orcid)0000-0001-8471-3224 Asin, Jesus Universidad de Zaragoza (orcid)0000-0002-0174-789X Cebrian, Ana C. Universidad de Zaragoza (orcid)0000-0002-9052-9674 Gelfand, Alan E. Abaurrea, Jesus Universidad de Zaragoza (orcid)0000-0002-7974-7435 2007 265 Universidad de Zaragoza Dpto. Métodos Estadísticos Área Estadís. Investig. Opera. 27 (2022), 487–505 J. agric. biol. environ. stat. JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS 1085-7117 1427673 http://zaguan.unizar.es/record/112406/files/texto_completo.pdf Versión publicada 1469171 http://zaguan.unizar.es/record/112406/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:112406 articulos driver 2024-03-18-13:50:05 ARTICLE