Advances in Time Series Methods and Applications: The A. Ian McLeod Festschrift (Fields Institute Communications Book 78)

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.-- Preface 5 Contents 7 Ian McLeod's Contribution to Time Series Analysis---A Tribute 9 1 Introduction 9 2 The Asymptotic Distribution of Residual Autocorrelation of the ARMA Models and the Portmanteau Test 10 3 Persistence---Long Memory Time Series Models 15 4 The Role of Duality in McLeod's Work 17 5 Water Resources and Intervention Analysis 19 6 Epilogue 21 References 21 The Doubly Adaptive LASSO for Vector Autoregressive Models 25 1 Introduction 26 2 The VAR(p) Process and Standard Modelling Procedure 28 3 The PLAC-Weighted Adaptive LASSO 31 3.1 The Adaptive LASSO 31 3.2 The Doubly Adaptive LASSO 32 4 The Asymptotic Properties of the PLAC-Weighted Adaptive LASSO 36 5 Computation Algorithm for the Doubly Adaptive LASSO 39 6 Monte Carlo Study 40 6.1 A Bivariate VAR(5) Process 41 6.2 A Trivariate VAR(5) Process 43 7 Real Data Analysis 46 8 Conclusion 47 References 53 On Diagnostic Checking Autoregressive Conditional Duration Models with Wavelet-Based Spectral Density Estimators 55 1 Introduction 56 2 Framework and Hypotheses 59 2.1 ACD Processes 59 2.2 Hypothesis of ACD Effects 60 2.3 Adequacy of ACD Models 62 3 Testing for ACD Effects 63 3.1 Wavelet Analysis 63 3.2 Test Statistics 65 3.3 Asymptotic Distribution 66 3.4 Adaptive Choice of the Finest Scale 68 4 Diagnostic Testing for ACD Models 71 4.1 Test Statistic 71 4.2 Asymptotic Distribution 73 4.3 Adaptive Choice of Finest Scale 73 5 Finite Sample Performance 76 5.1 Testing for ACD Effects 77 5.2 Testing for the Adequacy of an ACD Model 83 6 Application with Tick-by-Tick Trading Data 86 7 Conclusion 90 References 111 Diagnostic Checking for Weibull Autoregressive Conditional Duration Models 115 1 Introduction 115 2 A Portmanteau Test 116 2.1 Basic Definitions and the ML Estimation 116 2.2 The Main Result 118 3 Numerical Studies 119 3.1 Simulation Experiments 119 3.2 An Empirical Example 121 References 122 Diagnostic Checking for Partially Nonstationary Multivariate ARMA Models 123 1 Introduction 123 2 Partially Nonstationary Multivariate AR Models 124 3 Partially Nonstationary Multivariate ARMA Models 127 4 Main Results 129 5 Simulation Studies 132 6 Two Numerical Examples 136 References 138 The Portmanteau Tests and the LM Test for ARMA Models with Uncorrelated Errors 139 1 Introduction 139 2 Review of the Portmanteau Tests 141 2.1 The Portmanteau Test of Francq et al. [3] 142 2.2 The Portmanteau Test of Katayama [8] 143 2.3 The Portmanteau Test of Kuan and Lee [12] and Lee [13] 144 3 New Portmanteau Tests and LM Tests Using the KVB Approach 145 3.1 New Portmanteau Tests Using the KVB Approach 145 3.2 New LM Test Using the KVB Approach 147 4 Some Simulation Studies 149 4.1 Empirical Significance Level 149 4.2 Empirical Power 150 References 157 Generalized C(α) Tests for Estimating Functions with Serial Dependence 159 1 Introduction 160 2 Generalized C(α) Statistic 161 3 Distribution of the Generalized C(α) Statistic 164 4 Alternative C(α)-Type Statistics 167 5 Testing a Subvector 169 6 Two-Stage Procedures 173 6.1 Tests Based on General Two-Step Estimation 173 6.2 Tests Based on a Two-Step GMM Estimation 175 7 Conclusion 177 References 183 Regression Models for Ordinal Categorical Time Series Data 187 1 Introduction 187 2 Cumulative MDL Model for Ordinal Categorical Data 190 2.1 Marginal Cumulative Model at Time t=1 190 2.2 Lag 1 Transitional Cumulative Model at Time t=2,ƒ,T 191 3 Pseudo Binary Likelihood Estimation for the Ordinal Model 192 3.1 Likelihood Estimating Equations for the Regression Effects β 194 3.2 Likelihood Estimating Equations for the Dynamic Dependence Parameters γ 196 3.3 Joint Likelihood Estimating Equations for β and γ 197 4 Concluding Remarks 198 References 201 Identification of Threshold Autoregressive Moving Average Models 203 1 Introduction 203 2 Test Statistic and Its Asymptotic Distribution 205 2.1 Consistency of Least Squares Estimates 205 2.2 A Test Statistics for Threshold Nonlinearity 206 3 Building TARMA Models 208 3.1 Selecting the Delay Parameter d 208 3.2 Locating the Values of Thresholds 209 3.3 Modeling TARMA Models 210 4 Simulation Experiments and a Real Example 211 4.1 Simulation Experiments 211 4.2 A Real Example 216 5 Conclusion 219 References 221 Improved Seasonal Mann--Kendall Tests for Trend Analysis in Water Resources Time Series 223 1 Introduction 224 2 Null Distribution and Its Approximation 225 3 Simulation Results 228 4 Application 232 5 Discussion 232 References 236 A Brief Derivation of the Asymptotic Distribution of Pearson's Statistic and an Accurate Approximation to Its Exact Distribution 238 1 Introduction 238 2 A Short Proof of the Asymptotic Distribution of Pearson's χ2 statistic 239 3 An Accurate Approximation to the Exact Distribution of calP 241 4 Numerical Examples 242 5 Concluding Remarks 243 References 244 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 245 1 Introduction 245 2 Power Demand Forecasting and Industrial Adaptations to Shortages 246 2.1 Power Demand Forecasting 246 2.2 Power Shortages During Japan's 2011 Earthquake 247 3 Time Series Models and Index of Resilience 252 3.1 Time Series Model of Energy Demand 252 3.2 Approaches to Quantify the Resilience of Industrial Production During Power Shortages 253 4 Case Study of the 2011 Great East Japan Earthquake 254 4.1 Analysis of Severely Affected Region (Kanto) 254 4.2 Analysis per Industrial Sector 258 5 Conclusion 260 References 262 Atmospheric CO2 and Global Temperatures: The Strength and Nature of Their Dependence 264 1 The Series 264 2 Spectral Coherency Between the Series 266 3 A Standard VAR Model for the Series 270 4 A Structural VAR Model for the Climate Series 273 5 The Final Model, Its Interpretation and Properties 278 6 Conclusion 282 References 283 Catching Uncertainty of Wind: A Blend of Sieve Bootstrap and Regime Switching Models for Probabilistic Short-Term Forecasting of Wind Speed 284 1 Introduction 285 2 Data Description 286 3 Bootstrapped Regime Switching Model 287 4 Performance Measures for Probabilistic Forecasts 289 5 Case Study 290 6 Discussion 292 References 296 Front Matter....Pages i-viii Ian McLeod’s Contribution to Time Series Analysis—A Tribute....Pages 1-16 The Doubly Adaptive LASSO for Vector Autoregressive Models....Pages 17-46 On Diagnostic Checking Autoregressive Conditional Duration Models with Wavelet-Based Spectral Density Estimators....Pages 47-106 Diagnostic Checking for Weibull Autoregressive Conditional Duration Models....Pages 107-114 Diagnostic Checking for Partially Nonstationary Multivariate ARMA Models....Pages 115-130 The Portmanteau Tests and the LM Test for ARMA Models with Uncorrelated Errors....Pages 131-150 Generalized \(C(\alpha )\) Tests for Estimating Functions with Serial Dependence....Pages 151-178 Regression Models for Ordinal Categorical Time Series Data....Pages 179-194 Identification of Threshold Autoregressive Moving Average Models....Pages 195-214 Improved Seasonal Mann–Kendall Tests for Trend Analysis in Water Resources Time Series....Pages 215-229 A Brief Derivation of the Asymptotic Distribution of Pearson’s Statistic and an Accurate Approximation to Its Exact Distribution....Pages 231-237 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....Pages 239-257 Atmospheric \(\hbox {CO}_2\) and Global Temperatures: The Strength and Nature of Their Dependence....Pages 259-278 Catching Uncertainty of Wind: A Blend of Sieve Bootstrap and Regime Switching Models for Probabilistic Short-Term Forecasting of Wind Speed....Pages 279-293