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Analytical derivatives for Markov switching models / by Jeff Gable et al.: FB3-2/95-7E

This paper derives analytical gradients for a broad class of regime-switching models with Markovian state-transition probabilities. Such models are usually estimated by maximum likelihood methods, which require the derivatives of the likelihood function with respect to the parameter vector. These gradients are usually calculated by means of numerical techniques. The paper shows that analytical gradients considerably speed up maximum-likelihood estimation with no loss in accuracy. A sample program listing is included.--Abstract

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publications.gc.ca/pub?id=9.612490&sl=0

Publication information
Department/Agency
  • Bank of Canada.
TitleAnalytical derivatives for Markov switching models / by Jeff Gable et al.
Series title
  • Working paper 1192-5434 95-7
Publication typeMonograph - View Master Record
Language[English]
FormatPhysical text
Other formatsDigital text-[English]
Note(s)
  • "This paper derives analytical gradients for a broad class of regime-switching models with Markovian state-transition probabilities. Such models are usually estimated by maximum likelihood methods, which require the derivatives of the likelihood function with respect to the parameter vector. These gradients are usually calculated by means of numerical techniques. The paper shows that analytical gradients considerably speed up maximum-likelihood estimation with no loss in accuracy. A sample program listing is included."--Abstract.
  • Résumés en français
Publishing information
  • Ottawa - Ontario : Bank of Canada 1995.
BindingSoftcover
Description24p. : graphs, references, tables ; 28 cm.
ISBN0-662-23685-8
ISSN1192-5434
Catalogue number
  • FB3-2/95-7E
Subject terms
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