Prediction: Design of experiments based on approximating covariance kernels

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Description

Using Mercer`s expansion to approximate the covariance kernel of an observed random function the authors transform the prediction problem to the regression problem with random parameters. The latter one is considered in the framework of convex design theory. First they formulate results in terms of the regression model with random parameters, then present the same results in terms of the original problem.

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7 p.

Creation Information

Fedorov, V. November 1, 1998.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

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  • Oak Ridge National Laboratory
    Publisher Info: Oak Ridge National Lab., Computer Science and Mathematics Div., TN (United States)
    Place of Publication: Tennessee

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Description

Using Mercer`s expansion to approximate the covariance kernel of an observed random function the authors transform the prediction problem to the regression problem with random parameters. The latter one is considered in the framework of convex design theory. First they formulate results in terms of the regression model with random parameters, then present the same results in terms of the original problem.

Physical Description

7 p.

Notes

OSTI as DE99000244

Source

  • 3. St. Petersburg international workshop on simulation, St. Petersburg (Russian Federation), 28 Jun - 3 Jul 1998

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  • Other: DE99000244
  • Report No.: ORNL/CP--99704
  • Report No.: CONF-9806144--
  • Grant Number: AC05-96OR22464
  • Office of Scientific & Technical Information Report Number: 291086
  • Archival Resource Key: ark:/67531/metadc682641

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Creation Date

  • November 1, 1998

Added to The UNT Digital Library

  • July 25, 2015, 2:20 a.m.

Description Last Updated

  • Nov. 3, 2016, 6:50 p.m.

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Fedorov, V. Prediction: Design of experiments based on approximating covariance kernels, article, November 1, 1998; Tennessee. (digital.library.unt.edu/ark:/67531/metadc682641/: accessed September 22, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.