The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
Displaying 41 –
60 of
122
Proponemos una definición de "estabilidad" para un modelo bayesiano, respecto a cambios en la distribución básica (la distribución a priori se mantiene fija). Esta definición se discute e interpreta mediante el concepto de continuidad.Se obtienen también condiciones suficientes para la estabilidad así definida y se proponen algunos ejemplos.Finalmente se sugiere una generalización, con la distribución a priori también variable, y se obtiene un teorema para esta nueva situación.
En este artículo se estudia, desde una perspectiva bayesiana, un proceso AR(1) con errores exponenciales, ARE(1): para ello se construye una nueva familia de distribuciones conjugadas, denotada por CDG, que permite construir una especie de filtro de Kalman para la estimación recursiva de los parámetros del modelo.
El objetivo de este artículo es proponer una medida de incertidumbre asociada a un conjunto difuso, de un referencial finito, que generalice la entropía de Shannon; es decir, que además de considerar la distribución de probabilidades definida en el referencial considere también la función de pertenencia del conjunto difuso.Posteriormente se estudian algunas propiedades de la medida propuesta.
En este trabajo se desarrolla un método de comparación de experimentos con datos censurados. Dicho método se basa en la evaluación de la pérdida de información que se produce en estudios de supervivencia y fiabilidad cuando los tiempos de vida se censuran aleatoriamente por la derecha. Se supone que la distribución del tiempo de vida depende de un parámetro k-variante desconocido θ; y se usa la matriz de Fisher como medida de información apropiada acerca de θ. Se propone una medida matricial de...
Stein (1959), en su artículo sobre la gran discrepancia entre intervalos de confianza e intervalos fiduciales, puso de relieve el comportamiento poco convincente de la distribución inicial uniforme para el vector de medias de una normal mutivariante si nuestro interés se centra en hacer inferencias sobre el cuadrado de su norma.En este artículo, utilizando el método de la maximización de la información desconocida (Bernardo, 1979), se estudia en qué sentido la distribución inicial del vector de...
The problem considered is that of unbiased estimation for a two-parameter exponential distribution under time censored sampling. We obtain a necessary form of an unbiasedly estimable parametric function and prove that there does not exist any unbiased estimator of the parameters and the mean of the distribution. For reliability estimation at a specified time point, we give a necessary and sufficient condition for the existence of an unbiased estimator and suggest an unbiased estimator based on a...
The problem considered is that of unbiased estimation of reliability for a two-parameter exponential distribution under time censored sampling. We give necessary and sufficient conditions for the existence of uniformly minimum variance unbiased estimator and also provide a characterization of a complete class of unbiased estimators in situations where unbiased estimators exist.
We consider the problem of estimation of the value of a real-valued function u(θ), θ = (θ1, ..., θk)T, on the basis of a sample from non-truncated or truncated multivariate Modified Power Series Distributions. Using the general theory of estimation and the results of Patil (1965) and Patel (1978) we give the tables of MVUE's for functions of parameter θ of trinomial, multinomial, negative-multinomial and left-truncated modified power series distributions. We have applied the properties of MVUE's...
This paper introduces a new approach for the joint alignment of a large
collection of segmented images into the same system of coordinates while
estimating at the same time an optimal common coordinate system. The atlas
resulting from our group-wise alignment algorithm is obtained as the hidden
variable of an Expectation-Maximization (EM) estimation. This is achieved
by identifying the most consistent label across the collection of images at each
voxel in the common frame of coordinates.
In an...
We consider a model selection estimator of the covariance of a random process. Using the Unbiased Risk Estimation (U.R.E.) method, we build an estimator of the risk which allows to select an estimator in a collection of models. Then, we present an oracle inequality which ensures that the risk of the selected estimator is close to the risk of the oracle. Simulations show the efficiency of this methodology.
The aim of the paper is to show some possible statistical solution of the estimation of the dispersion of the GPS receiver. The presented method (based on theory of linear model with additional constraints of type I) can serve for an improvement of the accuracy of estimators of coordinates acquired from the GPS receiver.
The aim of the paper is to determine an influence of uncertainties in design and covariance matrices on estimators in linear regression model.
The reliable and effective assimilation of measurements and numerical simulations in engineering applications involving computational fluid dynamics is an emerging problem as soon as new devices provide more data. In this paper we are mainly driven by hemodynamics applications, a field where the progressive increment of measures and numerical tools makes this problem particularly up-to-date. We adopt a Bayesian approach to the inclusion of noisy data in the incompressible steady Navier-Stokes equations...
A large number of parameters in regression models can be serious obstacle for processing and interpretation of experimental data. One way how to overcome it is an elimination of some parameters. In some cases it need not deteriorate statistical properties of estimators of useful parameters and can help to interpret them. The problem is to find conditions which enable us to decide whether such favourable situation occurs.
Currently displaying 41 –
60 of
122