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Forecasting, structural time series models, and the Kalman filter /
This book is concerned with modelling economic and social time series and with addressing the special problems which the treatment of such series pose.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge ; New York :
Cambridge University Press,
1989.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Harvey, A. C. |q (Andrew C.) | |
| 245 | 1 | 0 | |a Forecasting, structural time series models, and the Kalman filter / |c Andrew Harvey. |
| 264 | 1 | |a Cambridge ; |a New York : |b Cambridge University Press, |c 1989. | |
| 300 | |a 1 online resource (xvi, 554 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references (pages 529-542) and indexes. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Cover; Half Title; TitlePage; Copyright; Contents; List of figures; Acknowledgement; Preface; Notation and conventions; List of abbreviations; 1 Introduction; 1.1 The nature of time series; 1.2 Explanatory variables and intervention analysis; 1.3 Multivariate models; 1.4 Statistical treatment; 1.5 Modelling methodology; 1.6 Forecasting; 1.7 Computer software; 2 Univariate time series models; 2.1 Introduction; 2.2 Ad hoc forecasting procedures; 2.3 The structure of time series models; 2.4 Stochastic properties; 2.5 ARIMA models and the reduced form; 2.6 ARIMA modelling; 2.7 Applications. | |
| 505 | 8 | |a Exercises3 State space models and the Kalman filter; 3.1 The state space form; 3.2 The Kalman filter; 3.3 Properties of time-invariant models; 3.4 Maximum likelihood estimation and the prediction errordecomposition; 3.5 Prediction; 3.6 Smoothing; 3.7 Non-linearity and non-normality; Appendix. Properties of the multivariate normal distribution; Exercises; 4 Estimation, prediction and smoothing for univariate structuraltime series models; 4.1 Application of the Kalman filter; 4.2 Estimation in the time domain; 4.3 Estimation in the frequency domain; 4.4 Identifiability. | |
| 505 | 8 | |a 4.5 Properties of estimators4.6 Prediction; 4.7 Estimation of components; Exercises; 5 Testing and model selection; 5.1 Principles of testing; 5.2 Lagrange multiplier tests; 5.3 Tests of specification for structural models; 5.4 Diagnostics; 5.5 Goodness of fit; 5.6 Post-sample predictive testing and model evaluation; 5.7 Strategy for model selection; Exercises; 6 Extensions of the univariate model; 6.1 Trends, detrending and unit roots; 6.2 Seasonality and seasonal adjustment; 6.3 Different timing intervals for the model and observations; 6.4 Data irregularities. | |
| 505 | 8 | |a 6.5 Time-varyingand non-linear models6.6 Non-normality, count data and qualitative observations; Exercises; 7 Explanatory variables; 7.1 Introduction; 7.2 Estimation in the frequency domain; 7.3 Estimation of models with explanatory variables andstructural time series components; 7.4 Tests and measures of goodness of fit; 7.5 Model selection strategy and applications; 7.6 Intervention analysis; 7.7 Time-varying parameters; 7.8 Instrumental variables; 7.9 Count data; Exercises; 8 Multivariate models; 8.1 Stochastic properties of multivariate models. | |
| 505 | 8 | |a 8.2 Seemingly unrelated time series equations8.3 Homogeneous systems; 8.4 Testing and model selection; 8.5 Dynamic factor analysis; 8.6 Intervention analysis with control groups; 8.7 Missing observations, delayed observations and contemporaneousaggregation; 8.8 Vector autoregressive models; 8.9 Simultaneous equation models; Exercises; 9 Continuous time; 9.1 Introduction; 9.2 Stock variables; 9.3 Flow variables; 9.4 Multivariate models; Appendix 1 Principal structural time series components and models; Appendix 2 Data sets; A. Energy demand of Other Final Users. | |
| 520 | |a This book is concerned with modelling economic and social time series and with addressing the special problems which the treatment of such series pose. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Time-series analysis. | |
| 650 | 0 | |a Kalman filtering. | |
| 650 | 6 | |a Série chronologique. | |
| 650 | 6 | |a Filtre de Kalman. | |
| 650 | 7 | |a MATHEMATICS |x Applied. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
| 650 | 7 | |a Techniques de prévision. |2 eclas | |
| 650 | 7 | |a Modèles économétriques. |2 eclas | |
| 650 | 7 | |a Kalman filtering |2 fast | |
| 650 | 7 | |a Time-series analysis |2 fast | |
| 650 | 7 | |a Kalman-Filter |2 gnd | |
| 650 | 7 | |a Zeitreihenanalyse |2 gnd | |
| 650 | 1 | 7 | |a Tijdreeksen. |2 gtt |
| 650 | 1 | 7 | |a Kalman-filters. |2 gtt |
| 650 | 1 | 7 | |a Modellen. |2 gtt |
| 650 | 1 | 7 | |a Prognoses. |2 gtt |
| 650 | 7 | |a Série chronologique. |2 ram | |
| 650 | 7 | |a Kalman, filtrage de. |2 ram | |
| 776 | 0 | 8 | |i Print version: |a Harvey, A.C. (Andrew C.). |t Forecasting, structural time series models, and the Kalman filter |z 9780521405737 |w (DLC) 89031417 |w (OCoLC)19458552 |
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