Constructing a Covariance Matrix that Yields a Specified Minimizer and a Specified Minimum Discrepancy Function Value.

Cudeck, Robert; Browne, Michael W.

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Peer reviewed

ERIC Number: EJ453850

Record Type: Journal

Publication Date: 1992

Pages: N/A

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ISSN: ISSN-0033-3123

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Constructing a Covariance Matrix that Yields a Specified Minimizer and a Specified Minimum Discrepancy Function Value.

Cudeck, Robert; Browne, Michael W.

Psychometrika, v57 n3 p357-69 Sep 1992

A method is proposed for constructing a population covariance matrix as the sum of a particular model plus a nonstochastic residual matrix, with the stipulation that the model holds with a prespecified lack of fit. The procedure is considered promising for Monte Carlo studies. (SLD)

Descriptors: Algorithms, Equations (Mathematics), Estimation (Mathematics), Factor Analysis, Goodness of Fit, Least Squares Statistics, Mathematical Models, Maximum Likelihood Statistics, Monte Carlo Methods, Psychometrics, Sampling

Publication Type: Journal Articles; Reports - Evaluative

Education Level: N/A

Audience: N/A

Language: English

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