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Annuncio ciclo di seminari
SEMINARI DEL DIPARTIMENTO DI SCIENZE STATISTICHE -- UNIVERSITA' DI PERUGIA
Lunedi' 3 marzo ore 17:00-18:00 Aula interna del Dipartimento
Speaker: Prof Avner Bar Hen, Universita' di Marsiglia
Titolo : A simple Goodness-of-fit Test for Parametric Regression
Models
Abstract :
A simple test is proposed for examining the adequacy of a family
of parametric models against nonparametric alternatives. The usual
diagnostic tools based on the residuals plots are useful but do
not lead to formal statistical tests. We propose a formal
statistical test that complements the graphical analysis.
Technically, the possible bias of the residuals of the parametric
fit is assumed to be a squared summable function of the predictive
variable and is decomposed along a family of orthogonal
polynomials. Our simulation studies indicate that this test
has a similar power as that of the adaptative Neyman test. Moreover,
it is simple to put on using usual statistical software and may be
easily extended to generalized linear and partial linear models.
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Martedi' 4 marzo ore 14:00- 15:00 Aula interna del Dipartimento
Speaker: Prof Annibale Biggeri, Universita' di Firenze
Titolo: Introduzione ai metodi statistici di analisi del genoma.
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Giovedi' 6 marzo 11:00-12:00 Aula interna del Dipartimento
Speaker: Prof Avner Bar Hen, Universita' di Marsiglia
Titolo: Mahalanobis distance is a common tool in discriminant analysis. We
present two extensions to the the case of mixed continuous and
discrete variables.
Abstract:
The first approach is based on Kullback-Leibler divergence. We study
statistical properties of these distance estimator, variables selection
and atypicality index (possibility that an individual is not coming from
one of the pre-determined populations).
The second approach consider that discrete variables are realizations
of non-observed continuous variables. This modelling is based on
generalized probit models. We consider the case where the
parameter of the model is estimated with exogeneous variables.
Quality os the estimation is study through simulations.
Both approaches are compared and results are applied to data for
varietal distinctivness.
Per informazioni:
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Elena Stanghellini
Dipartimento di Scienze Statistiche
Via A. Pascoli - C.P. 1315 Succ. 1
06100 Perugia (Italy)
Tel +39 075 5855229 or 5855242
Fax +39 075 5855950
email: elena.stanghellini@stat.unipg.it
home page: http://www.stat.unipg.it/DSS/elena.html
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