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Model selection for vector autoregressive processes.

by May So-Ching Lam. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 87-88). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The importance of Vector Time Series Analysis --- p.1 / Chapter 1.2 --- Objective --- p.3 / Chapter Chapter 2 --- Vector Autoregressive Models --- p.5 / Chapter 2.1 --- The VAR(p) models --- p.5 / Chapter 2.2 --- Least square estimation method --- p.7 / Chapter 2.3 --- VAR forecast --- p.9 / Chapter Chapter 3 --- Model Selection Criteria --- p.12 / Chapter 3.1 --- VAR order selection methods --- p.12 / Chapter 3.2 --- Hsiao's sequential method --- p.17 / Chapter 3.2.1 --- Two variables case --- p.19 / Chapter 3.2.2 --- Three variables case --- p.24 / Chapter Chapter 4 --- Illustrative Examples --- p.32 / Chapter Chapter 5 --- A Simulation Study --- p.37 / Chapter 5.1 --- Designs of experiments --- p.37 / Chapter 5.2 --- Simulation results --- p.47 / Chapter Chapter 6 --- Summary --- p.53 / Tables --- p.55 / References --- p.87

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_323122
Date January 2000
ContributorsLam, May So-Ching., Chinese University of Hong Kong Graduate School. Division of Statistics.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, 88 leaves ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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