Chapter

Algorithms for estimating parametric nonlinear models

Timo Teräsvirta, Dag Tjøstheim and W. J. Granger

in Modelling Nonlinear Economic Time Series

Published in print December 2010 | ISBN: 9780199587148
Published online May 2011 | e-ISBN: 9780191595387 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780199587148.003.0012

Series: Advanced Texts in Econometrics

Algorithms for estimating parametric nonlinear models

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This chapter contains an introduction to estimating parametric nonlinear models. Estimation has to be carried out using numerical algorithms. Both algorithms not using derivatives of the function to be optimized and ones requiring them are discussed. Several algorithms of both types are presented. The expectation‐maximization algorithm used for estimating Markov switching models and state space models is considered as well.

Keywords: EM algorithm; numerical optimization; genetic algorithm; gradient method; Newton‐Raphson algorithm; simulated annealing; variable metric method

Chapter.  10899 words. 

Subjects: Econometrics and Mathematical Economics

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