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Autor Pardo Llorente, Leandro |
Documentos disponibles escritos por este autor (104)
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In this paper the family of phi-divergence estimators for loglinear models with linear constraints and multinomial sampling is studied. This family is an extension of the maximum likelihood estimator studied by Haber and Brown (1986). A simulati[...]![]()
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Pardo Llorente, Julio Ángel ; Pardo Llorente, Leandro ; Zografos, Konstantinos | Elsevier Science | 2002This paper presents a minimum phi-divergence estimation procedure in multinomial models in which the probabilities depend on unknown parameters that are not mathematically independent but satisfy some functional relationships, This estimator is [...]![]()
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Cressie et al. (2000; 2003) introduced and studied a new family of statistics, based on the phi-divergence measure, for solving the problem of testing a nested sequence of loglinear models. In that family of test statistics the parameters are es[...]![]()
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Consider the loglinear model for categorical data under the assumption of either Poisson, multinomial, or product-multinomial sampling. We are interested in testing between various hypotheses on the parameter space. In this paper, the usual like[...]![]()
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Castilla González, Elena ; Martín Apaolaza, Nirian ; Pardo Llorente, Leandro ; Zografos, Konstantinos | https://www.mdpi.com/ | 2020This paper presents a model selection criterion in a composite likelihood framework based on density power divergence measures and in the composite minimum density power divergence estimators, which depends on an tuning parameter ?. After introd[...]![]()
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Batsidis, Apostolos ; Martín, Nirian ; Pardo Llorente, Leandro ; Zografos, Konstantinos | Gordon & Breach | 2014-01-02This paper presents a family of power divergence-type test statistics for testing the hypothesis of elliptical symmetry. We assess the performance of the new family of test statistics, using Monte Carlo simulation. In this context, the type I er[...]![]()
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Batsidis, Apostolos ; Martín, Nirian ; Pardo Llorente, Leandro ; Zografos, Konstantinos | Marcel Dekker Inc | 2013In a recent article, Cardoso de Oliveira and Ferreira have proposed a multivariate extension of the univariate chi-squared normality test, using a known result for the distribution of quadratic forms in normal variables. In this article, we prop[...]![]()
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In this paper we consider categorical data that are distributed according to a multinomial, product-multinomial or Poisson distribution whose expected values follow a log-linear model and we study the inference problem of hypothesis testing in a[...]![]()
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We study the minimum power-divergence estimator, introduced and studied by N. Cressie and T. R. C. Read [Multinomial goodness-of-fit tests. J. R. Stat. Soc., Ser. B 46, 440–464 (1984), in the loglinear model of quasi-independence. A simulation s[...]![]()
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It is usual to rely on the quasi-likelihood methods for deriving statistical methods applied to clustered multinomial data with no underlying distribution. Even though extensive literature can be encountered for these kind of data sets, there ar[...]![]()
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We consider the asymptotic distribution of divergence-based influence measures which are an extension for polytomous logistic regression of an influence measure proposed in Johnson (1985), for binary logistic regression. A numerical example comp[...]![]()
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In this article, a family of measures for detecting leverage cells in multinomial loglinear models based on Renyi's divergence measures is presented and its properties are studied. An example illustrates its behavior.![]()
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In this paper three families of test statistics for testing nonadditivity in loglinear models are presented under the assumption of either Poisson, multinomial, or product-multinomial sampling. These new families are based on the phi-divergence [...]![]()
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We consider minimum phi-divergence estimators (theta) over cap (phi)(n) of parameters theta of arbitrary dominated models mu(theta)![]()
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For the model of independence in a two way contingency table, shrinkage estimators based on minimum phi-divergence estimators and phi-divergence statistics are considered. These estimators are based on the James-Stein-type rule and incorporate t[...]