Applications of Computer Aided Time Series Modeling:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
1997
|
| Schriftenreihe: | Lecture Notes in Statistics
119 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | This book consists of three parts: Part One is composed of two introductory chapters. The first chapter provides an instrumental varible interpretation of the state space time series algorithm originally proposed by Aoki (1983), and gives an introductory account for incorporating exogenous signals in state space models. The second chapter, by Havenner, gives practical guidance in apply ing this algorithm by one of the most experienced practitioners of the method. Havenner begins by summarizing six reasons state space methods are advanta geous, and then walks the reader through construction and evaluation of a state space model for four monthly macroeconomic series: industrial production in dex, consumer price index, six month commercial paper rate, and money stock (Ml). To single out one of the several important insights in modeling that he shares with the reader, he discusses in Section 2ii the effects of sampling er rors and model misspecification on successful modeling efforts. He argues that model misspecification is an important amplifier of the effects of sampling error that may cause symplectic matrices to have complex unit roots, a theoretical impossibility. Correct model specifications increase efficiency of estimators and often eliminate this finite sample problem. This is an important insight into the positive realness of covariance matrices; positivity has been emphasized by system engineers to the exclusion of other methods of reducing sampling error and alleviating what is simply a finite sample problem. The second and third parts collect papers that describe specific applications |
| Beschreibung: | 1 Online-Ressource (VII, 335p) |
| ISBN: | 9781461222521 9780387947518 |
| ISSN: | 0930-0325 |
| DOI: | 10.1007/978-1-4612-2252-1 |
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Datensatz im Suchindex
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| author | Aoki, Masanao |
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| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4612-2252-1 |
| format | Electronic eBook |
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| spelling | Aoki, Masanao Verfasser aut Applications of Computer Aided Time Series Modeling edited by Masanao Aoki, Arthur M. Havenner New York, NY Springer New York 1997 1 Online-Ressource (VII, 335p) txt rdacontent c rdamedia cr rdacarrier Lecture Notes in Statistics 119 0930-0325 This book consists of three parts: Part One is composed of two introductory chapters. The first chapter provides an instrumental varible interpretation of the state space time series algorithm originally proposed by Aoki (1983), and gives an introductory account for incorporating exogenous signals in state space models. The second chapter, by Havenner, gives practical guidance in apply ing this algorithm by one of the most experienced practitioners of the method. Havenner begins by summarizing six reasons state space methods are advanta geous, and then walks the reader through construction and evaluation of a state space model for four monthly macroeconomic series: industrial production in dex, consumer price index, six month commercial paper rate, and money stock (Ml). To single out one of the several important insights in modeling that he shares with the reader, he discusses in Section 2ii the effects of sampling er rors and model misspecification on successful modeling efforts. He argues that model misspecification is an important amplifier of the effects of sampling error that may cause symplectic matrices to have complex unit roots, a theoretical impossibility. Correct model specifications increase efficiency of estimators and often eliminate this finite sample problem. This is an important insight into the positive realness of covariance matrices; positivity has been emphasized by system engineers to the exclusion of other methods of reducing sampling error and alleviating what is simply a finite sample problem. The second and third parts collect papers that describe specific applications Statistics Statistics, general Statistik Modellierung (DE-588)4170297-9 gnd rswk-swf Zeitreihe (DE-588)4127298-5 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Zeitreihe (DE-588)4127298-5 s Modellierung (DE-588)4170297-9 s 2\p DE-604 Havenner, Arthur M. Sonstige oth https://doi.org/10.1007/978-1-4612-2252-1 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Aoki, Masanao Applications of Computer Aided Time Series Modeling Statistics Statistics, general Statistik Modellierung (DE-588)4170297-9 gnd Zeitreihe (DE-588)4127298-5 gnd |
| subject_GND | (DE-588)4170297-9 (DE-588)4127298-5 (DE-588)4143413-4 |
| title | Applications of Computer Aided Time Series Modeling |
| title_auth | Applications of Computer Aided Time Series Modeling |
| title_exact_search | Applications of Computer Aided Time Series Modeling |
| title_full | Applications of Computer Aided Time Series Modeling edited by Masanao Aoki, Arthur M. Havenner |
| title_fullStr | Applications of Computer Aided Time Series Modeling edited by Masanao Aoki, Arthur M. Havenner |
| title_full_unstemmed | Applications of Computer Aided Time Series Modeling edited by Masanao Aoki, Arthur M. Havenner |
| title_short | Applications of Computer Aided Time Series Modeling |
| title_sort | applications of computer aided time series modeling |
| topic | Statistics Statistics, general Statistik Modellierung (DE-588)4170297-9 gnd Zeitreihe (DE-588)4127298-5 gnd |
| topic_facet | Statistics Statistics, general Statistik Modellierung Zeitreihe Aufsatzsammlung |
| url | https://doi.org/10.1007/978-1-4612-2252-1 |
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