Theory and Applications of Time Series Analysis and Forecasting : Selected Contributions from ITISE 2021 (Contributions to Statistics)

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Theory and Applications of Time Series Analysis and Forecasting : Selected Contributions from ITISE 2021 (Contributions to Statistics)

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  • 製本 Hardcover:ハードカバー版／ページ数 333 p.
  • 商品コード 9783031141966

Full Description

This book presents a selection of peer-reviewed contributions on the latest developments in time series analysis and forecasting, presented at the 7th International Conference on Time Series and Forecasting, ITISE 2021, held in Gran Canaria, Spain, July 19-21, 2021. It is divided into four parts. The first part addresses general modern methods and theoretical aspects of time series analysis and forecasting, while the remaining three parts focus on forecasting methods in econometrics, time series forecasting and prediction, and numerous other real-world applications. Covering a broad range of topics, the book will give readers a modern perspective on the subject.

The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics,statistics and econometrics.

Contents

- Part I Theoretical Aspects of Time Series. - An Improved Forecasting and Detection of Structural Breaks in Time Series Using Fuzzy Techniques. - Anomaly Detection Algorithm Using a Hybrid Modelling Approach for Energy Consumption Time Series. - Unit Root Test Combination via Random Forests. - Probabilistic Forecasting of Seasonal Time Series. - Nonstatistical Methods for Analysis, Forecasting, and Mining Time Series. - PMF Forecasting for Count Processes: A Comprehensive Performance Analysis. - A Novel First-Order Autoregressive Moving Average Model to Analyze Discrete-Time Series Irregularly Observed. - Part II Econometric and Forecasting. - Using Natural Language Processing to Measure COVID-19-Induced Economic Policy Uncertainty for Canada and the USA. - Asymptotic Expansions for Market Risk Assessment: Evidence in Energy and Commodity Indices. - Predicting Housing Prices for Spanish Regions. - Optimal Combination Forecast for Bitcoin Dollars Time Series. - The Impact of the Hungarian Retail Debt Program. - Predicting the Exchange Rate Path: The Importance of Using Up-to-Date Observations in the Forecasts. - Part III Time Series Prediction Applications. - Development of Algorithm for Forecasting System Software. - Forecasting High-Frequency Electricity Demand in Uruguay. - Day-Ahead Electricity Load Prediction Based on Calendar Features and Temporal Convolutional Networks. - Network Security Situation Awareness Forecasting Based on Neural Networks. - Part IV Advanced Applications in Time Series Analysis. - Modeling Covid-19 Contagion Dynamics: Time-Series Analysis Across Different Countries and Subperiods. - Diffusion of Renewable Energy for Electricity: An Analysis for Leading Countries. - The State and Perspectives of Employment in the Water Transport System of the Republic of Croatia. - Reversed STIRPAT Modeling: The Role of CO2 Emissions, Population, and Technology for a Growing Affluence.