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ISSN
0899-7667
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1530-888X
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2.21

Neural Computation

January 1, 2004, Vol. 16, No. 1, Pages 99-114
(doi: 10.1162/08997660460734010)
© 2003 Massachusetts Institute of Technology
On the Asymptotic Distribution of the Least-Squares Estimators in Unidentifiable Models
Article PDF (123.66 KB)
Abstract

In order to analyze the stochastic property of multilayered perceptrons or other learning machines, we deal with simpler models and derive the asymptotic distribution of the least-squares estimators of their parameters. In the case where a model is unidentified, we show different results from traditional linear models: the well-known property of asymptotic normality never holds for the estimates of redundant parameters.