Order estimation of high dimensional time series

Much research has focused on the problem of estimating the order of vector autoregressive (VAR) model and multivariate moving average (VMA) model. The most proposed solutions for this problem include Bayesian Information Criterion (BIC) and limiting spectral distribution of sample autocovariance mat...

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Main Author: Zeng, Shijia
Other Authors: Pan Guangming
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/156931
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1569312023-02-28T23:19:36Z Order estimation of high dimensional time series Zeng, Shijia Pan Guangming School of Physical and Mathematical Sciences GMPAN@ntu.edu.sg Science::Mathematics Much research has focused on the problem of estimating the order of vector autoregressive (VAR) model and multivariate moving average (VMA) model. The most proposed solutions for this problem include Bayesian Information Criterion (BIC) and limiting spectral distribution of sample autocovariance matrix. In this paper, two new approaches for order determination of VAR and VMA model are proposed. Maximum or sum of eigenvalues of sample autocovariance matrix is found to be able to select the order of VAR or VMA model. Another approach with the use of information criterion is also developed to select the order automatically. Time series data has been generated to examine the performance of two methods in existing work and two approaches proposed by ourselves. Bachelor of Science in Mathematical Sciences 2022-04-29T03:21:06Z 2022-04-29T03:21:06Z 2022 Final Year Project (FYP) Zeng, S. (2022). Order estimation of high dimensional time series. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156931 https://hdl.handle.net/10356/156931 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Mathematics
spellingShingle Science::Mathematics
Zeng, Shijia
Order estimation of high dimensional time series
description Much research has focused on the problem of estimating the order of vector autoregressive (VAR) model and multivariate moving average (VMA) model. The most proposed solutions for this problem include Bayesian Information Criterion (BIC) and limiting spectral distribution of sample autocovariance matrix. In this paper, two new approaches for order determination of VAR and VMA model are proposed. Maximum or sum of eigenvalues of sample autocovariance matrix is found to be able to select the order of VAR or VMA model. Another approach with the use of information criterion is also developed to select the order automatically. Time series data has been generated to examine the performance of two methods in existing work and two approaches proposed by ourselves.
author2 Pan Guangming
author_facet Pan Guangming
Zeng, Shijia
format Final Year Project
author Zeng, Shijia
author_sort Zeng, Shijia
title Order estimation of high dimensional time series
title_short Order estimation of high dimensional time series
title_full Order estimation of high dimensional time series
title_fullStr Order estimation of high dimensional time series
title_full_unstemmed Order estimation of high dimensional time series
title_sort order estimation of high dimensional time series
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/156931
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