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Non-linear regression for multiple time-series

Published online by Cambridge University Press:  14 July 2016

P. M. Robinson
P. M. Robinson*
Affiliation:
The Australian National University
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Abstract

A general multivariate non-linear regression model is considered, including as special cases linear regression when the regression matrix is of less than full rank, simultaneous equations systems and regression on an unobservable predetermined variable. Given a time-series of observations at unit intervals we consider the estimation of the parameters, subject to non-linear constraints, by minimizing a criterion based on the Fourier-transformed model. We allow the residuals to be generated by a stationary, linear, process and establish asymptotic properties of our estimates.

Keywords

NON-LINEAR MULTIVARIATE REGRESSIONSTATIONARY TIME-SERIESFOURIER METHODSSTRONG LAWCENTRAL LIMIT THEOREM
Type
Research Papers
Information
Journal of Applied Probability , Volume 9 , Issue 4 , December 1972 , pp. 758 - 768
Copyright
Copyright © Applied Probability Trust 1972 

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References

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