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Advances in Time Series Methods and Applications - The A. Ian McLeod Festschrift (Hardcover, 1st ed. 2016): Wai Keung Li, David... Advances in Time Series Methods and Applications - The A. Ian McLeod Festschrift (Hardcover, 1st ed. 2016)
Wai Keung Li, David A. Stanford, Hao Yu
R3,601 R2,889 Discovery Miles 28 890 Save R712 (20%) Ships in 12 - 17 working days

This volume reviews and summarizes some of A. I. McLeod's significant contributions to time series analysis. It also contains original contributions to the field and to related areas by participants of the festschrift held in June 2014 and friends of Dr. McLeod. Covering a diverse range of state-of-the-art topics, this volume well balances applied and theoretical research across fourteen contributions by experts in the field. It will be of interest to researchers and practitioners in time series, econometricians, and graduate students in time series or econometrics, as well as environmental statisticians, data scientists, statisticians interested in graphical models, and researchers in quantitative risk management.

Advances in Time Series Methods and Applications - The A. Ian McLeod Festschrift (Paperback, Softcover reprint of the original... Advances in Time Series Methods and Applications - The A. Ian McLeod Festschrift (Paperback, Softcover reprint of the original 1st ed. 2016)
Wai Keung Li, David A. Stanford, Hao Yu
R2,905 Discovery Miles 29 050 Ships in 10 - 15 working days

This volume reviews and summarizes some of A. I. McLeod's significant contributions to time series analysis. It also contains original contributions to the field and to related areas by participants of the festschrift held in June 2014 and friends of Dr. McLeod. Covering a diverse range of state-of-the-art topics, this volume well balances applied and theoretical research across fourteen contributions by experts in the field. It will be of interest to researchers and practitioners in time series, econometricians, and graduate students in time series or econometrics, as well as environmental statisticians, data scientists, statisticians interested in graphical models, and researchers in quantitative risk management.

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