000088401 001__ 88401
000088401 005__ 20210902121625.0
000088401 0247_ $$2doi$$a10.3390/sym12010020
000088401 0248_ $$2sideral$$a117041
000088401 037__ $$aART-2020-117041
000088401 041__ $$aeng
000088401 100__ $$aGouet, R.
000088401 245__ $$aStatistical Inference for the Weibull Distribution Based on delta-Record Data
000088401 260__ $$c2020
000088401 5060_ $$aAccess copy available to the general public$$fUnrestricted
000088401 5203_ $$aWe consider the maximum likelihood and Bayesian estimation of parameters and prediction of future records of the Weibull distribution from delta-record data, which consists of records and near-records. We discuss existence, consistency and numerical computation of estimators and predictors. The performance of the proposed methodology is assessed by Montecarlo simulations and the analysis of monthly rainfall series. Our conclusion is that inferences for the Weibull model, based on delta-record data, clearly improve inferences based solely on records. This methodology can be recommended, more so as near-records can be collected along with records, keeping essentially the same experimental design.
000088401 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E22$$9info:eu-repo/grantAgreement/ES/MINECO/MTM2017-83812-P
000088401 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000088401 590__ $$a2.713$$b2020
000088401 591__ $$aMULTIDISCIPLINARY SCIENCES$$b33 / 73 = 0.452$$c2020$$dQ2$$eT2
000088401 592__ $$a0.385$$b2020
000088401 593__ $$aChemistry (miscellaneous)$$c2020$$dQ2
000088401 593__ $$aPhysics and Astronomy (miscellaneous)$$c2020$$dQ2
000088401 593__ $$aMathematics (miscellaneous)$$c2020$$dQ2
000088401 593__ $$aComputer Science (miscellaneous)$$c2020$$dQ2
000088401 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000088401 700__ $$0(orcid)0000-0002-7615-2559$$aLopez, F.J.$$uUniversidad de Zaragoza
000088401 700__ $$0(orcid)0000-0003-1647-3462$$aMaldonado, L.$$uUniversidad de Zaragoza
000088401 700__ $$0(orcid)0000-0002-6474-2252$$aSanz, G.$$uUniversidad de Zaragoza
000088401 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera.
000088401 7102_ $$14008$$2623$$aUniversidad de Zaragoza$$bDpto. Estruc.Hª Econ.y Eco.Pb.$$cÁrea Métodos Cuant.Econ.Empres
000088401 773__ $$g12, 1 (2020), 20 [24 pp]$$pSymmetry (Basel)$$tSYMMETRY-BASEL$$x2073-8994
000088401 8564_ $$s386152$$uhttps://zaguan.unizar.es/record/88401/files/texto_completo.pdf$$yVersión publicada
000088401 8564_ $$s477230$$uhttps://zaguan.unizar.es/record/88401/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000088401 909CO $$ooai:zaguan.unizar.es:88401$$particulos$$pdriver
000088401 951__ $$a2021-09-02-08:49:31
000088401 980__ $$aARTICLE