Source:http://linkedlifedata.com/resource/pubmed/id/15006025
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
1
|
| pubmed:dateCreated |
2004-3-9
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| pubmed:abstractText |
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.
|
| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
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| pubmed:status |
MEDLINE
|
| pubmed:month |
Jan
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| pubmed:issn |
0899-7667
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| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
16
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
99-114
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| pubmed:meshHeading |
pubmed-meshheading:15006025-Algorithms,
pubmed-meshheading:15006025-Artificial Intelligence,
pubmed-meshheading:15006025-Least-Squares Analysis,
pubmed-meshheading:15006025-Linear Models,
pubmed-meshheading:15006025-Neural Networks (Computer),
pubmed-meshheading:15006025-Reproducibility of Results,
pubmed-meshheading:15006025-Stochastic Processes
|
| pubmed:year |
2004
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| pubmed:articleTitle |
On the asymptotic distribution of the least-squares estimators in unidentifiable models.
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| pubmed:affiliation |
Department of Information and Computer Engineering, Toyota National College of Technology, Toyota, Aichi, Japan. hayasaka@toyota-ct.ac.jp
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| pubmed:publicationType |
Journal Article
|