Consider a nonparametric Bayesian estimation problem where the Statistician has decided to use an exponential gamm aprocess prior. This paper deals with the selection problem of the process parameters. Some algorithm to determine the parameter c from the prior guess and the strength of belief are given. The case where this last concept changes with time is also studied.
In this paper the Kagan divergence measure is extended in order to establish a measure of the information that a random sample gives about a Dirichlet process as a whole. After studying some of its properties, the expression obtained in sampling from the step n to the step n+1 is given, and its Bayesian properties are studied. We finish proving the good behaviour of a stopping rule defined on the basis of the information obtained in sampling when passing from a step to the following.
We consider a measure of the diversity of a population based on the λ-measure of hypoentropy introduced by Ferreri (1980). Our purpose is to study its asymptotic distribution in a stratified sampling and its application to testing hypothesis. A numerical example based on real data is given.
This paper deals with Bayesian models given by statistical experiments and standard loss functions. Bayes probability of error and Bayes risk are estimated by means of classical and generalized information criteria applicable to the experiment. The accuracy of the estimation is studied. Among the information criteria studied in the paper is the class of posterior power entropies which include the Shannon entropy as special case for the power . It is shown that the most accurate estimate is in this...
Se plantea el problema de estimar una función de fiabilidad en el contexto bayesiano no paramétrico, pero utilizando técnicas paramétricas de estimación en procesos estocásticos. Se define el proceso gamma extendido, cuyas trayectorias son tasas de azar crecientes cuando se eligen convenientemente los parámetros del proceso. Se obtienen estimadores basados en este proceso, se estudian sus propiedades asintóticas bayesianas, y se termina con un ejemplo de aplicación mediante simulación.
It is known that direct-survey estimators of small area parameters, calculated with the data from the given small area, often present large mean squared errors because of small sample sizes in the small areas. Model-based estimators borrow strength from other related areas to avoid this problem. How small should domain sample sizes be to recommend the use of model-based estimators? How robust are small area estimators with respect to the rate
The problem of nonparametric estimation of a survival function based on a partially censored on the right sample is established in a Bayesian context, using parametric Bayesian techniques. Estimates are obtained considering neutral to the right processes, they are particularized to some of them, and their asymptotic properties are studied from a Bayesian point of view. Finally, an application to a Dirichlet process is simulated.
Se presenta un método de selección secuencial de un número fijo de experimentos a partir de las medidas de f*-divergencia introducidas por Csiszar (1967). Este trabajo es similar al desarrollado por De Groot (1970) con funciones de incertidumbre; sin embargo, no sólo se considera el problema de espacio paramétrico finito, sino que se estudia además el .
En Pardo (1984), se propuso un Plan de Muestreo Secuencial basado en la Energía Informacional (P.M.S.E.I.), análogo al propuesto por Lindley (1956, 1957) a partir de la Entropía de Shannon, con el fin de recoger información acerca de un parámetro desconocido θ. En esta comunicación se aplica el P.M.S.E.I. al caso concreto de la recogida de información acerca del parámetro θ de una distribución exponencial y se extiende el concepto de P.M.S.E.I. al caso en que el estadístico esté interesado en recoger...
In this work, a parametric sequential estimation method of survival functions is proposed in the Bayesian nonparametric context when neutral to the right processes are used. It is proved that the mentioned method is an 1-SLA rule when Dirichlet processes are used; furthermore, asymptotically pointwise optimal procedures are obtained. Finally, an example is given.
An asymptotic local power of Pearson chi-squared tests is considered, based on convex mixtures of the null densities with fixed alternative densities when the mixtures tend to the null densities for sample sizes This local power is used to compare the tests with fixed partitions of the observation space of small partition sizes with the tests whose partitions depend on and the partition sizes tend to infinity for . New conditions are presented under which it is asymptotically optimal...
En este trabajo se obtiene la distribución asintótica de la (r,s)-divergencia, introducida por Sharma y Mittal (1975), entre dos densidades f y f, cuando θ es fijo y θ desconocido o bien cuando los dos son desconocidos. Se supone que los parámetros desconocidos se estiman de acuerdo con el principio de máxima verosimilitud. Como caso particular se obtienen las distribuciones asintóticas en el caso de poblaciones multinomiales. Se concluye el trabajo construyendo, sobre la base de los estadísticos...
The aim of this review is to give different two-parametric generalizations of the following measures: directed divergence (Kullback and Leibler, 1951), Jensen difference divergence (Burbea and Rao 1982 a,b; Rao, 1982) and Jeffreys invariant divergence (Jeffreys, 1946). These generalizations are put in the unified expression and their properties are studied. The applications of generalized information and divergence measures to comparison of experiments and the connections with Fisher information...
We consider a measure of the diversity of a population based on the λ-measure of hypoentropy introduced by Ferreri (1980). Our purpose is to study its asymptotic distribution for testing hypotheses. A numerical example based on real data is given.
Burbea and Rao (1982a, 1982b) gave some general methods for constructing quadratic differential metrics on probability spaces. Using these methods, they obtained the Fisher information metric as a particular case. In this paper we apply the method based on entropy measures to obtain a Riemannian metric based on -entropy measures (Salicrú et al., 1993). The geodesic distances based on that information metric have been computed for a number of parametric families of distributions. The use of geodesic...
K. M. Wong and S. Chen [9] analyzed the Shannon entropy of a sequence of random variables under order restrictions. Using -entropies, I. J. Taneja [8], these results are generalized. Upper and lower bounds to the entropy reduction when the sequence is ordered and conditions under which they are achieved are derived. Theorems are presented showing the difference between the average entropy of the individual order statistics and the entropy of a member of the original independent identically distributed...
Disparities of discrete distributions are introduced as a natural and useful extension of the information-theoretic divergences. The minimum disparity point estimators are studied in regular discrete models with i.i.d. observations and their asymptotic efficiency of the first order, in the sense of Rao, is proved. These estimators are applied to continuous models with i.i.d. observations when the observation space is quantized by fixed points, or at random, by the sample quantiles of fixed orders....
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