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Semiparametric additive beta regression models: Inference and local influence diagnostics
dc.contributor.author | Ibacache-Pulgar, Germán | |
dc.contributor.author | Figueroa-Zúñiga, Jorge I. | |
dc.contributor.author | Marchant-Fuentes, Carolina | |
dc.date.accessioned | 2022-01-07T12:27:04Z | |
dc.date.available | 2022-01-07T12:27:04Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | http://repositorio.ucm.cl/handle/ucm/3703 | |
dc.description.abstract | In this paper, we study a semiparametric additive beta regression model using a parameterization based on the mean and a dispersion parameter. This model is useful for situations where the response variable is continuous and restricted to the unit interval, in addition to being related to other variables through a semiparametric regression structure. First, we formulate the model and then estimation of its parameters is discussed. A back-fitting algorithm is derived to attain the maximum penalized likelihood estimates by using natural cubic smoothing splines. We provide closed-form expressions for the score function, Fisher information matrix and its inverse. Local influence methods are derived as diagnostic tools. Finally, a practical illustration based real data is presented and discussed. | es_CL |
dc.language.iso | en | es_CL |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Chile | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | * |
dc.source | REVSTAT-Statistical Journal, 19(2), 255-274 | es_CL |
dc.subject | Beta distribution | es_CL |
dc.subject | Diagnostic techniques | es_CL |
dc.subject | Maximum penalized likelihood estimates | es_CL |
dc.subject | Penalized likelihood function | es_CL |
dc.subject | Semiparametric additive models | es_CL |
dc.title | Semiparametric additive beta regression models: Inference and local influence diagnostics | es_CL |
dc.type | Article | es_CL |
dc.ucm.facultad | Facultad de Ciencias Básicas | es_CL |
dc.ucm.indexacion | Scopus | es_CL |
dc.ucm.indexacion | Isi | es_CL |
dc.ucm.uri | www.ine.pt/revstat/pdf/REVSTAT_v19-n2-05.pdf | es_CL |
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