Consistency conditions on the least squares estimator in single common factor analysis model (Q1073507)
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scientific article; zbMATH DE number 3945121
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Consistency conditions on the least squares estimator in single common factor analysis model |
scientific article; zbMATH DE number 3945121 |
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Consistency conditions on the least squares estimator in single common factor analysis model (English)
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1986
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This paper is concerned with the consistency of estimators in a single common factor analysis model when the dimension of the observed vector is not fixed. In the model several conditions on the sample size n and the dimension p are established for the least squares estimator (L.S.E) to be consistent. Under some assumptions, p/n\(\to 0\) is a necessary and sufficient condition that the L.S.E. converges in probability to the true value. A sufficient condition for almost sure convergence is also given.
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dimension of observed vector
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convergence in probability
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covariance structure models
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consistency of estimators
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single common factor analysis model
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sample size
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least squares estimator
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sufficient condition for almost sure convergence
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0.89079607
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0.8745604
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0.8667425
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0.8654583
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