915 resultados para Automated estimator
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The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.
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Notification Services mediate between information publishers and consumers that wish to subscribe to periodic updates. In many cases, however, there is a mismatch between the dissemination of these updates and the delivery preferences of the consumer, often in terms of frequency of delivery, quality, etc. In this paper, we present an automated negotiation engine that identifies mutually acceptable terms; we study its performance, and discuss its application to a Grid Notification Service. We also demonstrate how the negotiation engine enables users to control the Quality of Service levels they require.
Resumo:
Notification Services mediate between information publishers and consumers that wish to subscribe to periodic updates. In many cases, however, there is a mismatch between the dissemination of these updates and the delivery preferences of the consumer, often in terms of frequency of delivery, quality, etc. In this paper, we present an automated negotiation engine that identifies mutually acceptable terms; we study its performance, and discuss its application to a Grid Notification Service. We also demonstrate how the negotiation engine enables users to control the Quality of Service levels they require.
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In this paper a state of the art of a system of automated deduction called SAD is described . An architecture of SAD corresponds well to a modern vision of the Evidence Algorithm programme, initiated by Academician V.Glushkov.
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This article explains these choices and their place in modern automated deduction.
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An underwater gas pipeline is the portion of the pipeline that crosses a river beneath its bottom. Underwater gas pipelines are subject to increasing dangers as time goes by. An accident at an underwater gas pipeline can lead to technological and environmental disaster on the scale of an entire region. Therefore, timely troubleshooting of all underwater gas pipelines in order to prevent any potential accidents will remain a pressing task for the industry. The most important aspect of resolving this challenge is the quality of the automated system in question. Now the industry doesn't have any automated system that fully meets the needs of the experts working in the field maintaining underwater gas pipelines. Principle Aim of this Research: This work aims to develop a new system of automated monitoring which would simplify the process of evaluating the technical condition and decision making on planning and preventive maintenance and repair work on the underwater gas pipeline. Objectives: Creation a shared model for a new, automated system via IDEF3; Development of a new database system which would store all information about underwater gas pipelines; Development a new application that works with database servers, and provides an explanation of the results obtained from the server; Calculation of the values MTBF for specified pipelines based on quantitative data obtained from tests of this system. Conclusion: The new, automated system PodvodGazExpert has been developed for timely and qualitative determination of the physical conditions of underwater gas pipeline; The basis of the mathematical analysis of this new, automated system uses principal component analysis method; The process of determining the physical condition of an underwater gas pipeline with this new, automated system increases the MTBF by a factor of 8.18 above the existing system used today in the industry.
Resumo:
In this paper, we propose a two-step estimator for panel data models in which a binary covariate is endogenous. In the first stage, a random-effects probit model is estimated, having the endogenous variable as the left-hand side variable. Correction terms are then constructed and included in the main regression.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)