Intro
Preface
Contents
Advanced Statistical and Mathematical Methods for Time Series Analysis
Random Forest Variable Selection for Sparse Vector Autoregressive Models
1 Introduction
2 State of the Art
2.1 Feature Selection in Vector Autoregressive Models
2.2 Random Forest for Feature Filtering
3 Methodology and Data
3.1 Methods
3.2 Data: Urban Traffic Forecasting
4 Results
5 Discussion
6 Conclusions
References
Covariance Functions for Gaussian Laplacian Fields in Higher Dimension
1 Introduction

2 Frequency Domain Treatment of Stationary Fields in Higher Dimensions
2.1 Covariance Functions of Laplacian Fields
2.2 AR(p)
2.3 ARMA Fields
3 Appendix
References
The Correspondence Between Stochastic Linear Difference and Differential Equations
1 Introduction: The Discrete-Continuous Correspondence
2 ARMA Estimation and the Effects of Over-Rapid Sampling
3 Sinc Function Interpolation and Fourier Interpolation
4 Discrete-Time and Continuous-Time Models
5 ARMA Model and Its Continuous-Time CARMA Counterpart

6 Stochastic Differential Equations Driven by Wiener Processes
7 Summary and Conclusions
References
New Test for a Random Walk Detection Based on the Arcsine Law
1 Introduction
1.1 Random Walk
1.2 Ordinary Random Walk Test
1.3 Random Walk Test for an AR(1) Process
2 Efficiency Evaluation of the Proposed Test
2.1 Gaussian Random Walk
2.2 Gaussian Mixture Model
3 Power Evaluation of the Proposed Test
3.1 An AR(1) Process with the Gaussian Innovations
3.2 An AR(1) Process with the Student-T Innovations
4 Conclusions
References

Econometric Models and Forecasting
On the Automatic Identification of Unobserved Components Models
1 Introduction
2 Unobserved Components Models
2.1 Trend Components
2.2 Seasonal Components
2.3 Irregular Components
3 State-Space Systems
4 Automatic Forecasting Algorithm for UC
5 Case Studies
5.1 Monthly Average Temperatures in Madrid at El Retiro Weather Station
5.2 Spanish Gross Domestic Product (GDP)
5.3 Demand Database
6 Conclusions
References

Spatial Integration of Pig Meat Markets in the EU: Complex Network Analysis of Non-linear Price Relationships
1 Introduction
2 Data and Methods
2.1 Data
2.2 Filtering
2.3 Non-linear Granger Causality Networks
2.4 Network Measures
2.5 Temporal Network Evolution
3 Finite Sample Properties of the GAM-Test
4 Empirical Analysis and Results
4.1 Network Measures of Individual Node Connectivity
4.2 Measures of Global Network Cohesiveness and Their Evolution
5 Conclusion
References