Advances in Time Series Methods and Applications

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).