Asymptotic optimality of experimental designs in estimating a product of means.
Bayes robustness via the Kolmogorov metric
An upper bound for the Kolmogorov distance between the posterior distributions in terms of that between the prior distributions is given. For some likelihood functions the inequality is sharp. Applications to assessing Bayes robustness are presented.
Bayes sequential estimation procedures for exponential-type processes
The Bayesian sequential estimation problem for an exponential family of processes is considered. Using a weighted square error loss and observing cost involving a linear function of the process, the Bayes sequential procedures are derived.
Bayes sharpening of imprecise information
A complete algorithm is presented for the sharpening of imprecise information, based on the methodology of kernel estimators and the Bayes decision rule, including conditioning factors. The use of the Bayes rule with a nonsymmetrical loss function enables the inclusion of different results of an under- and overestimation of a sharp value (real number), as well as minimizing potential losses. A conditional approach allows to obtain a more precise result thanks to using information entered as the...
Bayesian analysis of structural change in a distributed Lag Model (Koyck Scheme)
Structural change for the Koyck Distributed Lag Model is analyzed through the Bayesian approach. The posterior distribution of the break point is derived with the use of the normal-gamma prior density and the break point, ν, is estimated by the value that attains the Highest Posterior Probability (HPP). Simulation study is done using R. Given the parameter values ϕ = 0.2 and λ = 0.3, the full detection of the structural change when σ² = 1 is generally attained at ν + 1. The after...
Bayesian inference in group judgement formulation and decision making using qualitative controlled feedback.
This paper considers the problem of making statistical inferences about group judgements and group decisions using Qualitative Controlled Feedback, from the Bayesian point of view. The qualitative controlled feedback procedure was first introduced by Press (1978), for a single question of interest. The procedure in first reviewed here including the extension of the model to the multiple question case. We develop a model for responses of the panel on each stage. Many questions are treated simultaneously...
Bayesian methods in hydrology: a review.
Hydrology and water resources management are inherently affected by uncertainty in many of their involved processes, including inflows, rainfall, water demand, evaporation, etc. Statistics plays, therefore, an essential role in their study. We review here some recent advances within Bayesian statistics and decision analysis which will have a profound impact in these fields.
Bayesian testing of fuzzy parametric hypotheses from fuzzy information
Change-Point problems: approaches and applications.
Problems of making inferences about abrupt changes in the mechanism underlying a sequence of observations are considered in both retrospective and on-line contexts. Among the topics considered are the Lindisfarne scribes problem; switching straight lines; manoeuvering targets, and shifts of level or slope in linear time series models. Summary analyses of data obtained in studies of schizophrenic and kidney transplant patients are presented.
Comments on: Natural Induction: An objective Bayesian approach.
Compatibilidad del método de De Groot para llegar a un consenso con la fórmula de Bayes.
En este artículo se prueba que el sencillo método propuesto por De Groot para llegar a un consenso cuando los varios decisores tienen opiniones diferentes expresadas en términos de distribuciones de probabilidad es compatible con la regla de Bayes cuando se tiene en cuenta la información muestral. Se demuestra que si se calculan primero las distribuciones a posteriori y después se aplica el método de De Groot para alcanzar un consenso (cuando esto sea posible), es lo mismo que realizar primero el...
Convexity inequalities for estimating generalized conditional entropies from below
Generalized entropic functionals are in an active area of research. Hence lower and upper bounds on these functionals are of interest. Lower bounds for estimating Rényi conditional -entropy and two kinds of non-extensive conditional -entropy are obtained. These bounds are expressed in terms of error probability of the standard decision and extend the inequalities known for the regular conditional entropy. The presented inequalities are mainly based on the convexity of some functions. In a certain...
Cross additivity - an application
We try to show that Discriminant Analysis can be considered as a branch of Statistical Decision Theory when viewed from a Bayesian approach. First we present the necessary measure theory results, next we briefly outline the foundations of Bayesian Inference before developing Discriminant Analysis as an application of Bayesian Estimation. Our approach renders Discriminant Analysis more flexible since it gives the possibility of classing an element as belonging to a group of populations. This possibility...
Decision making in an incompletely known stochastic system, II
Decision making in an incompletely known stochastic system, I
Design Considerations for Neyman-Pearson and Wald Hypothesis Testing.
Discontinuity, decision and conflict.
The motivation for this paper arises out of the authors experiences in modelling real decision makers where the decisions show not only a continuous response to a continuously changing environment but also sudden or discontinuous changes. The theoretical basis involves a parametric characterisation of the environment, a decision makers perception of it in terms of a twice differentiable Distribution Function and a bounded Loss Function. Under a specified minimizing dynamic, the resultant Expected...
Diseño muestral óptimo en el caso de no respuesta.
Se propone un modelo predictivo para analizar situaciones de no respuesta. El modelo es, en cierto sentido, secuencial y se describe desde la teoría de la decisión bayesiana. El modelo permite considerar opiniones y experiencia previa sobre la proporción de unidades que no responden al primer contacto, diferenciar y relacionar entre unidades que responden y unidades que no responden, costo de obtener información de las unidades que no respondieron, etc. Se analizan las decisiones referentes a seleccionar...
Estimación bayesiana múltiple de un parámetro.
The problem to be analyzed in this paper deals with the finding of n values x1, x2, ..., xn ∈ R which minimize the function:E [míni=1,...,n c (ξ - xi)]where ξ is a one-dimensional random variable with known distribution function φ and c is a measurable and positive function.First, conditions on c in order to ensure the existence of a solution to this problem are determined. Next, necessary conditions to be satisfied by the point (x1, x2, ..., xn) in which the function attains the minimum are looked...
Estimating normal density and normal distribution function: is Kolmogorov's estimator admissible?
The statistical estimation problem of the normal distribution function and of the density at a point is considered. The traditional unbiased estimators are shown to have Bayes nature and admissibility of related generalized Bayes procedures is proved. Also inadmissibility of the unbiased density estimator is demonstrated.