1,214 research outputs found
Generalized information criteria for Bayes decisions
summary: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 class achieved by the quadratic posterior entropy of the power . The paper introduces and studies also a new class of alternative power entropies which in general estimate the Bayes errors and risk more tightly than the classical power entropies. Concrete examples, tables and figures illustrate the obtained results
Analytic and bootstrap approximations of prediction errors under a multivariate fay-herriot model
A Multivariate Fay-Herriot model is used to aid the prediction of small area parameters of dependent variables with sample data aggregated to area level. The empirical best linear unbiased predictor of the parameter vector is used, and an approximation of the elements of the mean cross product error matrix is obtained by an extension of the results of Prasad and Rao (1990) to the multiparameter case. Three different bootstrap approximations of those elements are introduced, and a simulation study is developed in order to compare the efficiency of all presented approximations, including a comparison under lack of normality. Further, the number of replications needed for the bootstrap procedures to get stabilized are studied
Resultados de los esfuerzos innovadores en Venezuela y Colombia: un etudio comparativo
ResumenLas patentes son el resultado de los esfuerzos innovadores. Para entender dicho procesoen Colombia y Venezuela, se plantea compararlas durante el perÃodo 1990-2006.Se usan las bases de datos de la Red Iberoamericana de Ciencia y TecnologÃa y de laOficina de Patentes de los Estados Unidos para obtener la información. Los resultadosindican que: (i) Venezuela supera a Colombia hasta por ocho veces durante el perÃodo1990-2006, (ii) el tipo de industria al cual Venezuela dirige sus esfuerzos es el sectorde QuÃmica y Metalurgia y Colombia al de Necesidades Humanas, (iii) en ambospaÃses las empresas que más innovaciones producen pertenecen al sector público (iv)su alcance en Venezuela es más amplio que en Colombia, y (v) existe desigualdad degénero entre los inventores que patentan en ambos paÃses.Palabras Clave: Patentes, Innovación, AméricaPatentes, Innovación, América Latina.
A comparative study of small area estimators
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 small area estimators are with respect to the rate sample size/number of domains? To give answers or recommendations about the questions above, a Monte Carlo simulation experiment is carried out. In this simulation study, model-based estimators for small areas are compared with some standard design-based estimators. The simulation study starts with the construction of an artificial population data file, imitating a census file of an Statistical Office. A stratified random design is used to draw samples from the artificial population. Small area estimators of the mean of a continuous variable are calculated for all small areas and compared by using different performance measures. The evolution of this performance measures is studied when increasing the number of small areas, which means to decrease their sizes
Value Chain: From iDMU to Shopfloor Documentation of Aeronautical Assemblies
Competition in the aerospace manufacturing companies has led them
to continuously improve the efficiency of their processes from the conceptual
phase to the start of production and during operation phase, providing services to
clients. PLM (Product Lifecycle Management) is an end-to-end business solution
which aims to provide an environment of information about the product and
related processes available to the whole enterprise throughout the product’s lifecycle.
Airbus designs and industrializes aircrafts using Concurrent Engineering
methods since decades. The introduction of new PLM methods, procedures and
tools, and the need to improve processes efficiency and reduce time-to-market,
led Airbus to pursue the Collaborative Engineering method. Processes efficiency
is also impacted by the variety of systems existing within Airbus. Interoperability
rises as a solution to eliminate inefficiencies due to information exchange and
transformations and it also provides a way to discover and reuse existing information.
The ARIADNE project (Value chain: from iDMU to shopfloor documentation
of aeronautical assemblies) was launched to support the industrialization
process of an aerostructure by implementing the industrial Digital Mock-Up
(iDMU) concept in a Collaborative Engineering framework. Interoperability
becomes an important research workpackage in ARIADNE to exploit and reuse
the information contained in the iDMU and to create the shop floor documentation.
This paper presents the context, the conceptual approach, the methodology
adopted and preliminary results of the project
Extensions of the parametric families of divergences used in statistical inference
summary:We propose a simple method of construction of new families of %-divergences. This method called convex standardization is applicable to convex and concave functions twice continuously differentiable in a neighborhood of with nonzero second derivative at the point . Using this method we introduce several extensions of the LeCam, power, and Matusita divergences. The extended families are shown to connect smoothly these divergences with the Kullback divergence or they connect various pairs of these particular divergences themselves. We investigate also the metric properties of divergences from these extended families
Small area estimation of poverty indicators under partitioned area-level time models
This paper deals with small area estimation of poverty indicators. Small area estimators of these quantities are derived from partitioned time-dependent area-level linear mixed models. The introduced models are useful for modelling the different behaviour of the target variable by sex or any other dichotomic characteristic. The mean squared errors are estimated by explicit formulas. An application to data from the Spanish Living Conditions Survey is given
Small area estimation of poverty indicators under partitioned area-level time models
This paper deals with small area estimation of poverty indicators. Small area estimators of these quantities are derived from partitioned time-dependent area-level linear mixed models. The introduced models are useful for modelling the different behaviour of the target variable by sex or any other dichotomic characteristic. The mean squared errors are estimated by explicit formulas. An application to data from the Spanish Living Conditions Survey is given
Small area estimation of poverty indicators under partitioned area-level time models
This paper deals with small area estimation of poverty indicators. Small area estimators of these quantities are derived from partitioned time-dependent area-level linear mixed models. The introduced models are useful for modelling the different behaviour of the target variable by sex or any other dichotomic characteristic. The mean squared errors are estimated by explicit formulas. An application to data from the Spanish Living Conditions Survey is given.Peer Reviewe
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