Name
Title | ||
|---|---|---|
Construction of Covariance Matrices with a Specified Discrepancy Function Minimizer, with Application to Factor Analysis |
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 inferences of misspecified models. We analyze theoretical aspects of the problem and suggest a numerical procedure based on semidefinite programming techniques. As an example, we discuss in detail the factor analysis model. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1137/080735515 | SIAM J. Matrix Analysis Applications |
Keywords | Field | DocType |
specified discrepancy function minimizer,covariance matrices,semidefinite programming technique,corresponding minimizer,discrepancy function,numerical procedure,factor analysis,covariance structural model,covariance matrix,monte carlo study,main goal,factor analysis model,misspecified model,semidefinite programming,generalized least squares,maximum likelihood | Discrepancy function,Monte Carlo method,Covariance function,Mathematical optimization,Matrix (mathematics),Covariance matrix,Analysis of covariance,Semidefinite programming,Mathematics,Covariance | Journal |
Volume | Issue | ISSN |
31 | 4 | 0895-4798 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| So Yeon Chun | 1 | 10 | 2.74 |
| Alexander Shapiro | 2 | 1273 | 147.62 |