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Time Series: Data Analysis and Theory.
Abstract
This book will be most useful to applied mathematicians, communication engineers, signal processors, statisticians, and time series researchers, both applied and theoretical. Readers should have some background in complex function theory and matrix algebra and should have successfully completed the equivalent of an upper division course in statistics.
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Citations
Cited by
Principal component analysis: A review and recent developments
Jolliffe, I. T., & Cadima, J. (2016) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2015.0202 · Cited by 10,117
Bispectrum estimation: A digital signal processing framework
Nikias, C. L., & Raghuveer, M. R. (1987) · Proceedings of the IEEE · doi:10.1109/proc.1987.13824 · Cited by 1,377
Performance analysis of Root-Music
Rao, B. D., & Hari, K. V. S. (1989) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/29.45540 · Cited by 992
Undirected graphs of frequency-dependent functional connectivity in whole brain networks
Salvador, R., Suckling, J., Schwarzbauer, C., & Bullmore, E. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1645 · Cited by 437
Quantile cointegrating regression
Xiao, Z. (2009) · Journal of Econometrics · doi:10.1016/j.jeconom.2008.12.005 · Cited by 431
Metadata
- Authors
- Brillinger, D. R.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1981-12
- Volume
- 37
- Issue
- 4
- Pages
- 869
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W2797925168
- Cited by
- 799
- References
- 0
- FWCI
- 4.21
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
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- CoChat. (2026). Citation check: Time Series: Data Analysis and Theory. https://app.cochat.ai/papers/10.2307/2530198
- The paper
- Brillinger, D. R. (1981). Time Series: Data Analysis and Theory. Biometrics. https://doi.org/10.2307/2530198
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.
