Exact properties of the maximum likelihood estimator in exponential regression models: a differential geometry approach
Exact properties of the maximum likelihood estimator in exponential regression models: a differential geometry approach
Using recently developed methods for obtaining exact distribution results for implicitly defined estimators, we study the exact properties of the maximum likelihood estimator in exponential regression models. The main technical problem is the evaluation of a surface integral over an n-k)-dimensional hyperplane embedded in the n-dimensional sample space. Details of the calculation are given for the cases k = 1 and k = 2 and some general properties of the densities for arbitrary k are indicated.
University of Southampton
Hillier, G.H.
3423bd61-c35f-497e-87a3-6a5fca73a2a1
O'Brien, R.J.
6d46f2be-6f1d-4bcd-9b94-baedee23ff22
1999
Hillier, G.H.
3423bd61-c35f-497e-87a3-6a5fca73a2a1
O'Brien, R.J.
6d46f2be-6f1d-4bcd-9b94-baedee23ff22
Hillier, G.H. and O'Brien, R.J.
(1999)
Exact properties of the maximum likelihood estimator in exponential regression models: a differential geometry approach
(Discussion Papers in Economics and Econometrics, 9901)
Southampton, UK.
University of Southampton
33pp.
Record type:
Monograph
(Discussion Paper)
Abstract
Using recently developed methods for obtaining exact distribution results for implicitly defined estimators, we study the exact properties of the maximum likelihood estimator in exponential regression models. The main technical problem is the evaluation of a surface integral over an n-k)-dimensional hyperplane embedded in the n-dimensional sample space. Details of the calculation are given for the cases k = 1 and k = 2 and some general properties of the densities for arbitrary k are indicated.
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9901.pdf
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Published date: 1999
Additional Information:
Also a book chapter:
Applications of differential geometry to econometrics book contents
Pages: 85 - 118
Year of Publication: 2000
ISBN:0-201-70039-5
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Local EPrints ID: 33136
URI: http://eprints.soton.ac.uk/id/eprint/33136
PURE UUID: 12af523c-dd8c-4634-9e40-c4297a9c08ca
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Date deposited: 28 Jun 2007
Last modified: 16 Mar 2024 02:42
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