Ebook: Time Series: Theory and Methods

This paperback edition is a reprint of the 1991 edition.

Time Series: Theory and Methods is a systematic account of linear time series models and their application to the modeling and prediction of data collected sequentially in time. The aim is to provide specific techniques for handling data and at the same time to provide a thorough understanding of the mathematical basis for the techniques. Both time and frequency domain methods are discussed, but the book is written in such a way that either approach could be emphasized. The book is intended to be a text for graduate students in statistics, mathematics, engineering, and the natural or social sciences. It contains substantial chapters on multivariate series and state-space models (including applications of the Kalman recursions to missing-value problems) and shorter accounts of special topics including long-range dependence, infinite variance processes, and nonlinear models.

Most of the programs used in the book are available in the modeling package ITSM2000, the student version of which can be downloaded from http://www.stat.colostate.edu/~pjbrock/student06.

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This paperback edition is a reprint of the 1991 edition.

Time Series: Theory and Methods is a systematic account of linear time series models and their application to the modeling and prediction of data collected sequentially in time. The aim is to provide specific techniques for handling data and at the same time to provide a thorough understanding of the mathematical basis for the techniques. Both time and frequency domain methods are discussed, but the book is written in such a way that either approach could be emphasized. The book is intended to be a text for graduate students in statistics, mathematics, engineering, and the natural or social sciences. It contains substantial chapters on multivariate series and state-space models (including applications of the Kalman recursions to missing-value problems) and shorter accounts of special topics including long-range dependence, infinite variance processes, and nonlinear models.

Most of the programs used in the book are available in the modeling package ITSM2000, the student version of which can be downloaded from http://www.stat.colostate.edu/~pjbrock/student06.

---

This paperback edition is a reprint of the 1991 edition.

Time Series: Theory and Methods is a systematic account of linear time series models and their application to the modeling and prediction of data collected sequentially in time. The aim is to provide specific techniques for handling data and at the same time to provide a thorough understanding of the mathematical basis for the techniques. Both time and frequency domain methods are discussed, but the book is written in such a way that either approach could be emphasized. The book is intended to be a text for graduate students in statistics, mathematics, engineering, and the natural or social sciences. It contains substantial chapters on multivariate series and state-space models (including applications of the Kalman recursions to missing-value problems) and shorter accounts of special topics including long-range dependence, infinite variance processes, and nonlinear models.

Most of the programs used in the book are available in the modeling package ITSM2000, the student version of which can be downloaded from http://www.stat.colostate.edu/~pjbrock/student06.

Content:
Front Matter....Pages i-xvi
Stationary Time Series....Pages 1-41
Hilbert Spaces....Pages 42-76
Stationary ARMA Processes....Pages 77-113
The Spectral Representation of a Stationary Process....Pages 114-165
Prediction of Stationary Processes....Pages 166-197
Asymptotic Theory....Pages 198-217
Estimation of the Mean and the Autocovariance Function....Pages 218-237
Estimation for ARMA Models....Pages 238-272
Model Building and Forecasting with ARIMA Processes....Pages 273-329
Inference for the Spectrum of a Stationary Process....Pages 330-400
Multivariate Time Series....Pages 401-462
State-Space Models and the Kalman Recursions....Pages 463-505
Further Topics....Pages 506-553
Back Matter....Pages 555-579

---

This paperback edition is a reprint of the 1991 edition.

Time Series: Theory and Methods is a systematic account of linear time series models and their application to the modeling and prediction of data collected sequentially in time. The aim is to provide specific techniques for handling data and at the same time to provide a thorough understanding of the mathematical basis for the techniques. Both time and frequency domain methods are discussed, but the book is written in such a way that either approach could be emphasized. The book is intended to be a text for graduate students in statistics, mathematics, engineering, and the natural or social sciences. It contains substantial chapters on multivariate series and state-space models (including applications of the Kalman recursions to missing-value problems) and shorter accounts of special topics including long-range dependence, infinite variance processes, and nonlinear models.

Most of the programs used in the book are available in the modeling package ITSM2000, the student version of which can be downloaded from http://www.stat.colostate.edu/~pjbrock/student06.

Content:
Front Matter....Pages i-xvi
Stationary Time Series....Pages 1-41
Hilbert Spaces....Pages 42-76
Stationary ARMA Processes....Pages 77-113
The Spectral Representation of a Stationary Process....Pages 114-165
Prediction of Stationary Processes....Pages 166-197
Asymptotic Theory....Pages 198-217
Estimation of the Mean and the Autocovariance Function....Pages 218-237
Estimation for ARMA Models....Pages 238-272
Model Building and Forecasting with ARIMA Processes....Pages 273-329
Inference for the Spectrum of a Stationary Process....Pages 330-400
Multivariate Time Series....Pages 401-462
State-Space Models and the Kalman Recursions....Pages 463-505
Further Topics....Pages 506-553
Back Matter....Pages 555-579
....