Time Series Analysis and Forecasting

Selected Contributions from the ITISE Conference

  • Ignacio Rojas
  • Héctor Pomares
Conference proceedings

Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Table of contents

  1. Front Matter
    Pages i-xix
  2. Advanced Analysis and Forecasting Methods

    1. Front Matter
      Pages 1-1
    2. Teresa Scholz, Frank Raischel, Pedro G. Lind, Matthias Wächter, Vitor V. Lopes, Bernd Lehle
      Pages 3-11
    3. Mahayaudin M. Mansor, Max E. Glonek, David A. Green, Andrew V. Metcalfe
      Pages 13-25
    4. Thorsten Dickhaus, Markus Pauly
      Pages 27-45
    5. Pedro Carpena, Ana V. Coronado, Concepción Carretero-Campos, Pedro Bernaola-Galván, Plamen Ch. Ivanov
      Pages 89-102
  3. Theoretical and Applied Econometrics

    1. Front Matter
      Pages 103-103
    2. José Aureliano Martín Segura, César Pérez López, José Luis Navarro Espigares
      Pages 105-112
    3. María Antonia Navascués, Maria Victoria Sebastián, Miguel Latorre
      Pages 113-122
    4. Mária Bohdalová, Michal Greguš
      Pages 123-133
    5. Maria da Conceição Costa, Manuel G. Scotto, Isabel Pereira
      Pages 189-202
  4. Applications in Time Series Analysis and Forecasting

  5. Machine Learning Techniques in Time Series Analysis and Prediction

  6. María Antonia Navascués, Maria Victoria Sebastián, Mario Latorre
    Pages E1-E1

About these proceedings


This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems.

The International Work-Conferences on Time Series (ITISE) provide a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.


37M10, 62M10, 62-XX, 68-XX, 60-XX, 58-XX, 37-XX time series analysis forecasting applications in computer science applications in econometrics applications in industry big data high-dimensional data on-line learning real-life problems statistical methods for time series machine learning

Editors and affiliations

  • Ignacio Rojas
    • 1
  • Héctor Pomares
    • 2
  1. 1.CITIC-UGRUniversity of GranadaGranadaSpain
  2. 2.CITIC-UGRUniversity of GranadaGranadaSpain

Bibliographic information