The Pure and Applied Mathematics (한국수학교육학회지시리즈B:순수및응용수학)
- Volume 2 Issue 2
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- Pages.133-140
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- 1995
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- 1226-0657(pISSN)
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- 2287-6081(eISSN)
QR DECOMPOSITION IN NONLINEAR EXPERIMENTAL DESIGN
- Oh, Im-Geol (Department of Computer Sciences and Statics, Han-seo University)
- Published : 1995.12.01
Abstract
The D-optimal design criterion for precise parameter estimation in nonlinear regression analysis is called the determinant criterion because the determinant of a matrix is to be maximized. In this thesis, we derive the gradient and the Hessian of the determinant criterion, and apply a QR decomposition for their efficient computations. We also propose an approximate form of the Hessian matrix which can be calculated from the first derivative of a model function with respect to the design variables. These equations can be used in a Gauss-Newton type iteration procedure.
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