title: A Conditional Least Squares Approach to Bilinear Time Series Estimation
creator: Grahn, Thorsten
subject: ddc-510
subject: 510 Mathematics
description: In this paper we develop a Conditional Least Squares (CLS) procedurefor estimating bilinear time series models. We apply this method to twogeneral types of bilinear models. A model of type I is a special superdiagonalbilinear model which includes the linear ARMA model as a submodel. A model oftype II is a standardized version of the popular bilinear BL(p,0,p,1) model(see e.g. Liu and Chen (1990), Sesay and Subba Rao (1991)). For both models weshow that the limiting distribution of the resulting CLS estimates is Gaussianand the law of the iterated logarithm holds.
date: 1993-04
type: Working paper
type: info:eu-repo/semantics/workingPaper
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/21354/1/beitrag.06.pdf
identifier: DOI:10.11588/heidok.00021354
identifier: urn:nbn:de:bsz:16-heidok-213545
identifier:   Grahn, Thorsten  (1993) A Conditional Least Squares Approach to Bilinear Time Series Estimation.  [Working paper]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/21354/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: eng