Influence diagnostics for elliptical semiparametric mixed models
| Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
|---|---|
| Data(s) |
21/10/2013
21/10/2013
2012
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| Resumo |
In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates. CAPES CAPES CNPq CNPq FAPESP (Brazil) FAPESP, Brazil FONDECYT (Chile) FONDECYT-Chile [1070919] |
| Identificador |
STATISTICAL MODELLING, LONDON, v. 12, n. 2, supl. 1, Part 3, pp. 165-193, APR, 2012 1471-082X http://www.producao.usp.br/handle/BDPI/35275 10.1177/1471082X1001200203 |
| Idioma(s) |
eng |
| Publicador |
SAGE PUBLICATIONS LTD LONDON |
| Relação |
STATISTICAL MODELLING |
| Direitos |
restrictedAccess Copyright SAGE PUBLICATIONS LTD |
| Palavras-Chave | #ELLIPTICAL DISTRIBUTIONS #MAXIMUM PENALIZED LIKELIHOOD ESTIMATES #NONPARAMETRIC MODELS #ROBUST ESTIMATES #SENSITIVITY ANALYSIS #LINEAR-REGRESSION MODELS #LOCAL INFLUENCE #LONGITUDINAL DATA #T-DISTRIBUTION #PENALIZED LIKELIHOOD #ROBUST ESTIMATION #SMOOTHING SPLINE #EM ALGORITHM #VARIANCE #STATISTICS & PROBABILITY |
| Tipo |
article original article publishedVersion |
