<div class="csl-bib-body">
<div class="csl-entry">Deistler, M., & Scherrer, W. (2022). <i>Time Series Models</i> (Vol. 224). Springer Nature. https://doi.org/10.1007/978-3-031-13213-1</div>
</div>
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dc.identifier.isbn
978-3-031-13212-4
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dc.identifier.isbn
978-3-031-13213-1
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/135925
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dc.description.abstract
Provides an understanding of core parts of multivariate time series theory and models. Presents a self-contained exposition with numerous examples and exercises. Emphasizes weakly stationary processes and linear dynamic models.
en
dc.language.iso
en
-
dc.publisher
Springer Nature
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dc.relation.ispartofseries
Lecture Notes in Statistics
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dc.subject
Time Series
en
dc.subject
Stationary Processes
en
dc.subject
Linear Dynamic Models
en
dc.subject
Forecasting
en
dc.subject
Spectral Analysis
en
dc.title
Time Series Models
-
dc.type
Book
en
dc.type
Buch
de
dc.contributor.affiliation
TU Wien, Austria
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dc.relation.issn
0930-0325
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dc.type.category
Monograph
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dc.relation.eissn
2197-7186
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tuw.container.volume
224
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tuw.peerreviewed
true
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tuw.relation.ispartofseries
Lecture Notes in Statistics
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tuw.relation.publisher
Springer Nature
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Schweiz
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A4
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C6
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A3
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Mathematical Methods in Economics
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Modeling and Simulation
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Fundamental Mathematics Research
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50
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25
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25
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E105-02 - Forschungsbereich Ökonometrie und Systemtheorie
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tuw.publisher.doi
10.1007/978-3-031-13213-1
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201
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0000-0003-3949-6229
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Mathematik
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1010
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100
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E105 - Institut für Stochastik und Wirtschaftsmathematik
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E105 - Institut für Stochastik und Wirtschaftsmathematik
