A monte carlo study on two methods of calculating the mle's covariance matrix in a seemingly unrelated nonlinear regression.*

DOI10.1080/07474939508800323zbMath0825.62946OpenAlexW2083853010MaRDI QIDQ4853102

Mark J. Jensen

Publication date: 13 December 1995

Published in: Econometric Reviews (Search for Journal in Brave)

Full work available at URL: https://mpra.ub.uni-muenchen.de/39020/1/MPRA_paper_39020.pdf

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) General nonlinear regression (62J02)

Cites Work

• Unnamed Item
• Least squares and maximum likelihood estimation of non-linear systems
• On the efficient computation of the nonlinear full-information maximum- likelihood estimator
• Seemingly unrelated nonlinear regressions
• Maximum Likelihood and Iterated Aitken Estimation of Nonlinear Systems of Equations
• A Rapidly Convergent Descent Method for Minimization
• An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias

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