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Time Series Analysis and Forecasting

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Cover of 'Time Series Analysis and Forecasting'

Table of Contents

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    Book Overview
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    Chapter 1 A Direct Method for the Langevin-Analysis of Multidimensional Stochastic Processes with Strong Correlated Measurement Noise
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    Chapter 2 Threshold Autoregressive Models for Directional Time Series
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    Chapter 3 Simultaneous Statistical Inference in Dynamic Factor Models
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    Chapter 4 The Relationship Between the Beveridge–Nelson Decomposition and Exponential Smoothing
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    Chapter 5 Permutation Entropy and Order Patterns in Long Time Series
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    Chapter 6 Generative Exponential Smoothing and Generative ARMA Models to Forecast Time-Variant Rates or Probabilities
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    Chapter 7 First-Passage Time Properties of Correlated Time Series with Scale-Invariant Behavior and with Crossovers in the Scaling
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    Chapter 8 The Environmental Impact of Economic Activity on the Planet
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    Chapter 9 Stock Indices in Emerging and Consolidated Economies from a Fractal Perspective
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    Chapter 10 Value at Risk with Filtered Historical Simulation
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    Chapter 11 A SVEC Model to Forecast and Perform Structural Analysis (Shocks) for the Mexican Economy, 1985Q1–2014Q4
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    Chapter 12 Intraday Data vs Daily Data to Forecast Volatility in Financial Markets
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    Chapter 13 Predictive and Descriptive Qualities of Different Classes of Models for Parallel Economic Development of Selected EU-Countries
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    Chapter 14 Search and Evaluation of Stock Ranking Rules Using Internet Activity Time Series and Multiobjective Genetic Programming
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    Chapter 15 Integer-Valued APARCH Processes
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    Chapter 16 Emergency-Related, Social Network Time Series: Description and Analysis
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    Chapter 17 Competitive Models for the Spanish Short-Term Electricity Demand Forecasting
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    Chapter 18 Age-Specific Death Rates Smoothed by the Gompertz–Makeham Function and Their Application in Projections by Lee–Carter Model
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    Chapter 19 An Application of Time Series Analysis in Judging the Working State of Ground-Based Microwave Radiometers and Data Calibration
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    Chapter 20 Identifying the Best Performing Time Series Analytics for Sea Level Research
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    Chapter 21 Modellation and Forecast of Traffic Series by a Stochastic Process
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    Chapter 22 Spatio-Temporal Modeling for fMRI Data
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    Chapter 23 Communicating Artificial Neural Networks with Physical-Based Flow Model for Complex Coastal Systems
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    Chapter 24 Forecasting Daily Water Demand Using Fuzzy Cognitive Maps
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    Chapter 25 Forecasting Short-Term Demand for Electronic Assemblies by Using Soft-Rules
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    Chapter 26 Electrical Load Forecasting: A Parallel Seasonal Approach
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    Chapter 27 A Compounded Multi-resolution-Artificial Neural Network Method for the Prediction of Time Series with Complex Dynamics
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    Chapter 28 Erratum to: Stock Indices in Emerging and Consolidated Economies from a Fractal Perspective
Attention for Chapter 12: Intraday Data vs Daily Data to Forecast Volatility in Financial Markets
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