Advances in Time Series Methods and Applications

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.

Discusses a diverse range of state-of-the-art topics in time series analysis Contains contributions from a number of researchers renowned for their time series work Covers applications, methodologies, and theory Accessible to researchers, practitioners, and graduate students Includes supplementary material: sn.pub/extras

Texte du rabat
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.

Contenu

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).