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Forecasting, structural time series models and the kalman filter
Abstract
This book is concerned with modelling economic and social time series and with addressing the special problems which the treatment of such series pose.
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Cited by
Power and performance management of virtualized computing environments via lookahead control
Kusic, D., Kephart, J. O., Hanson, J. E., Kandasamy, N., & Jiang, G. (2009) · Cluster Computing · doi:10.1007/s10586-008-0070-y · Cited by 699
Handling Missing Data in the Modeling of Intensive Longitudinal Data
Ji, L., Chow, S.-M., Schermerhorn, A. C., Jacobson, N. C., & Cummings, E. M. (2018) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1080/10705511.2017.1417046 · Cited by 74
Jacobson, N. C., Chow, S.-M., & Newman, M. G. (2019) · Behavior Research Methods · doi:10.3758/s13428-018-1101-0 · Cited by 63
A Primer on Two-Level Dynamic Structural Equation Models for Intensive Longitudinal Data
McNeish, D. (2018) · doi:10.31234/osf.io/j56bm · Cited by 12
Metadata
- Authors
- Harvey, A. C.
- Venue
- Wilmott
- Publisher
- Wilmott Magazine Ltd
- Published
- 2002-12
- Volume
- 2002
- Issue
- 1
- Pages
- 14-15
- ISSN
- 1540-6962 (ISSN-L)
- 1541-8286
- OpenAlex
- W1992819453
- Cited by
- 398
- References
- 0
- FWCI
- 25.45
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Forecasting, structural time series models and the kalman filter. https://app.cochat.ai/papers/10.1002/wilm.42820020109
- The paper
- Harvey, A. C. (2002). Forecasting, structural time series models and the kalman filter. Wilmott. https://doi.org/10.1002/wilm.42820020109
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
