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Prediction intervals and lack-of-fit tests for neural networks

Posted on:1999-01-21Degree:Ph.DType:Dissertation
University:Kansas State UniversityCandidate:Ballou, Lynda LeeFull Text:PDF
GTID:1468390014469637Subject:Statistics
Abstract/Summary:
This purpose of this dissertation is to determine if a typical lack-of-fit test used in regression modeling where the data contain true replicates or near replicates can be used to select an adequate model for a model created with a neural network program and to determine the reliability of the predictions from a model created by a neural network program. Also provided is a brief overview of artificial neural networks and some interesting aspects of neural network programs discovered during a simulation study involving three different neural network programs namely Braincel, Ripley's S+ program, and Nychka's S+ program.
Keywords/Search Tags:Neural network
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