Construction of Covariance Matrices with a specified Discrepancy Function Minimizer, with Application to Factor Analysis
So Yeon Chun (gth586amail.gatech.edu)
Abstract: The main goal of this paper is to develop a numerical procedure for construction of covariance matrices such that for a given covariance structural model and a discrepancy function the corresponding minimizer of the discrepancy function has a specified value. Often construction of such matrices is a first step in Monte Carlo studies of statistical in- ferences of misspecified models. We analyze theoretical aspects of the problem, and suggest a numerical procedure based on semi-definite programming techniques. As an example, we discuss in details the factor analysis model.
Keywords: Model misspecification, covariance structure analysis, maximum likelihood, generalized least squares, discrepancy function, factor analysis, semi-definite programming.
Category 1: Applications -- OR and Management Sciences
Citation: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205, USA, 06/2008
Entry Submitted: 06/13/2008
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