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Advances in time series methods and ...

Li, Wai Keung.

Advances in time series methods and applicationsthe A. Ian Mcleod festschrift /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in time series methods and applicationsedited by Wai Keung Li, David A. Stanford, Hao Yu.
Reminder of title:	the A. Ian Mcleod festschrift /
other author:	Li, Wai Keung.
Published:	New York, NY :Springer New York :2016.
Description:	viii, 293 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Time-series analysis.
Online resource:	http://dx.doi.org/10.1007/978-1-4939-6568-7
ISBN:	9781493965687$q(electronic bk.)

Advances in time series methods and applicationsthe A. Ian Mcleod festschrift /
Advances in time series methods and applicationsthe A. Ian Mcleod festschrift /[electronic resource] :edited by Wai Keung Li, David A. Stanford, Hao Yu. - New York, NY :Springer New York :2016. - viii, 293 p. :ill., digital ;24 cm. - Fields institute communications,v.781069-5265 ;. - Fields institute communications ;v.63..

1. Ian McLeod's Contribution to Time Series Analysis: a Tribute (W.K. Li) -- 2. The Doubly Adaptive LASSO for Vector Autoregressive Models (Z.Z. Liu, R. Kulperger, H. Yu) -- 3. On diagnostic checking autoregressive conditional duration models with wavelet-based spectral density estimators (P. Duchesne, Y. Hong) -- 4. Diagnostic checking for Weibull autoregressive conditional duration models (Y. Zheng, Y. Li, W.K. Li, G. Li) -- 5. Diagnostic checking for Partially Nonstationary Multivariate ARMA Models (M.T. Tai, Y.X. Yang, and S.Q. Ling) -- 6. The portmanteau tests and the LM test for ARMA models with uncorrelated errors (N. Katayama) -- 7. Generalized C(alpha) tests for estimating functions with serial dependence J.-M. Dufour, A. Tognon, P. Tuvaandorj) -- Regression Models for Ordinal Categorical Time Series Data (B.C. Sutradhar, R.P. Rao) -- 9. Identification of Threshold Autoregressive Moving Average Models (Q. Xia, H. Wong) -- 10. Improved Seasonal Mann-Kendall Tests for Trend Analysis in Water Resources Time Series (Y. Zhang, P. Cabilio and K. Nadeem) -- 11. A brief derivation of the asymptotic distribution of Pearson's statistic and an accurate approximation to its exact distribution (S.B. Provost) -- 12. Business Resilience during Power Shortages: A Power Saving Rate Measured by Power Consumption Time Series in Industrial Sector before and after the Great East Japan Earthquake in 2011 (Y. Kajitani) -- Atmospheric CO2 and global temperatures: the strength and nature of their dependence (G. Tunnicliffe Wilson) -- Catching Uncertainty of Wind: A Blend of Sieve Bootstrap and Regime Switching Models for Probabilistic Short-term Forecasting of Wind Speed (Y.R. Gel, V. Lyubchich, S.E. Ahmed)

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.

ISBN: 9781493965687$q(electronic bk.)

Standard No.: 10.1007/978-1-4939-6568-7doiSubjects--Topical Terms:

181890
Time-series analysis.

LC Class. No.: QA280

Dewey Class. No.: 519.55

Advances in time series methods and applicationsthe A. Ian Mcleod festschrift /
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505 0 $a 1. Ian McLeod's Contribution to Time Series Analysis: a Tribute (W.K. Li) -- 2. The Doubly Adaptive LASSO for Vector Autoregressive Models (Z.Z. Liu, R. Kulperger, H. Yu) -- 3. On diagnostic checking autoregressive conditional duration models with wavelet-based spectral density estimators (P. Duchesne, Y. Hong) -- 4. Diagnostic checking for Weibull autoregressive conditional duration models (Y. Zheng, Y. Li, W.K. Li, G. Li) -- 5. Diagnostic checking for Partially Nonstationary Multivariate ARMA Models (M.T. Tai, Y.X. Yang, and S.Q. Ling) -- 6. The portmanteau tests and the LM test for ARMA models with uncorrelated errors (N. Katayama) -- 7. Generalized C(alpha) tests for estimating functions with serial dependence J.-M. Dufour, A. Tognon, P. Tuvaandorj) -- Regression Models for Ordinal Categorical Time Series Data (B.C. Sutradhar, R.P. Rao) -- 9. Identification of Threshold Autoregressive Moving Average Models (Q. Xia, H. Wong) -- 10. Improved Seasonal Mann-Kendall Tests for Trend Analysis in Water Resources Time Series (Y. Zhang, P. Cabilio and K. Nadeem) -- 11. A brief derivation of the asymptotic distribution of Pearson's statistic and an accurate approximation to its exact distribution (S.B. Provost) -- 12. Business Resilience during Power Shortages: A Power Saving Rate Measured by Power Consumption Time Series in Industrial Sector before and after the Great East Japan Earthquake in 2011 (Y. Kajitani) -- Atmospheric CO2 and global temperatures: the strength and nature of their dependence (G. Tunnicliffe Wilson) -- Catching Uncertainty of Wind: A Blend of Sieve Bootstrap and Regime Switching Models for Probabilistic Short-term Forecasting of Wind Speed (Y.R. Gel, V. Lyubchich, S.E. Ahmed)
520 $a 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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