eprintid: 21354
rev_number: 12
eprint_status: archive
userid: 2326
dir: disk0/00/02/13/54
datestamp: 2016-06-20 09:10:41
lastmod: 2016-06-21 09:28:28
status_changed: 2016-06-20 09:10:41
type: workingPaper
metadata_visibility: show
creators_name: Grahn, Thorsten
title: A Conditional Least Squares Approach to Bilinear Time Series Estimation
subjects: ddc-510
divisions: i-110400
keywords: Estimation; bilinear time series; central limit theorem; law of the iterated logarithm; conditional moments
abstract: 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
id_scheme: DOI
id_number: 10.11588/heidok.00021354
schriftenreihe_cluster_id: sr-10a
schriftenreihe_order: 06
ppn_swb: 1657248224
own_urn: urn:nbn:de:bsz:16-heidok-213545
language: eng
bibsort: GRAHNTHORSACONDITION199304
full_text_status: public
place_of_pub: Heidelberg
pages: 47
citation:   Grahn, Thorsten  (1993) A Conditional Least Squares Approach to Bilinear Time Series Estimation.  [Working paper]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/21354/1/beitrag.06.pdf