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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[...]texto impreso
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 [...]texto impreso
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[...]texto impreso
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[...]texto impreso
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[...]texto impreso
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[...]texto impreso
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[...]texto impreso
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[...]texto impreso
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[...]texto impreso
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[...]texto impreso
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[...]texto impreso
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.texto impreso
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 [...]texto impreso
We consider minimum phi-divergence estimators (theta) over cap (phi)(n) of parameters theta of arbitrary dominated models mu(theta)texto impreso
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[...]