Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156931
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dc.contributor.authorZeng, Shijiaen_US
dc.date.accessioned2022-04-29T03:21:06Z-
dc.date.available2022-04-29T03:21:06Z-
dc.date.issued2022-
dc.identifier.citationZeng, S. (2022). Order estimation of high dimensional time series. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156931en_US
dc.identifier.urihttps://hdl.handle.net/10356/156931-
dc.description.abstractMuch 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.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectScience::Mathematicsen_US
dc.titleOrder estimation of high dimensional time seriesen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorPan Guangmingen_US
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.description.degreeBachelor of Science in Mathematical Sciencesen_US
dc.contributor.supervisoremailGMPAN@ntu.edu.sgen_US
item.grantfulltextrestricted-
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Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)
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