Estimation of Conditional Quantile using Neural Networks

P. Kulczycki, Henrik Schiøler

Publikation: Bidrag til tidsskriftTidsskriftartikelFormidling

Resumé

The problem of estimating conditional quantiles using neural networks is investigated here. A basic structure is developed using the methodology of kernel estimation, and a theory guaranteeing con-sistency on a mild set of assumptions is provided. The constructed structure constitutes a basis for the design of a variety of different neural networks, some of which are considered in detail. The task of estimating conditional quantiles is related to Bayes point estimation whereby a broad range of applications within engineering, economics and management can be suggested. Numerical results illustrating the capabilities of the elaborated neural network are also given.
OriginalsprogDansk
TidsskriftPeriodica Polytechnica
Sider (fra-til)109-126
StatusUdgivet - 1999

Citer dette

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Estimation of Conditional Quantile using Neural Networks. / Kulczycki, P.; Schiøler, Henrik.

I: Periodica Polytechnica, 1999, s. 109-126.

Publikation: Bidrag til tidsskriftTidsskriftartikelFormidling

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AB - The problem of estimating conditional quantiles using neural networks is investigated here. A basic structure is developed using the methodology of kernel estimation, and a theory guaranteeing con-sistency on a mild set of assumptions is provided. The constructed structure constitutes a basis for the design of a variety of different neural networks, some of which are considered in detail. The task of estimating conditional quantiles is related to Bayes point estimation whereby a broad range of applications within engineering, economics and management can be suggested. Numerical results illustrating the capabilities of the elaborated neural network are also given.

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