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Modeling and Stochastic Learning for Forecasting in High Dimensions

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Cover of 'Modeling and Stochastic Learning for Forecasting in High Dimensions'

Table of Contents

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    Book Overview
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    Chapter 1 Short Term Load Forecasting in the Industry for Establishing Consumption Baselines: A French Case
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    Chapter 2 Confidence Intervals and Tests for High-Dimensional Models: A Compact Review
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    Chapter 3 Modelling and Forecasting Daily Electricity Load via Curve Linear Regression
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    Chapter 4 Constructing Graphical Models via the Focused Information Criterion
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    Chapter 5 Fully Nonparametric Short Term Forecasting Electricity Consumption
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    Chapter 6 Forecasting Electricity Consumption by Aggregating Experts; How to Design a Good Set of Experts
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    Chapter 7 Flexible and Dynamic Modeling of Dependencies via Copulas
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    Chapter 8 Online Residential Demand Reduction Estimation Through Control Group Selection
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    Chapter 9 Forecasting Intra Day Load Curves Using Sparse Functional Regression
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    Chapter 10 Modelling and Prediction of Time Series Arising on a Graph
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    Chapter 11 Massive-Scale Simulation of Electrical Load in Smart Grids Using Generalized Additive Models
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    Chapter 12 Spot Volatility Estimation for High-Frequency Data: Adaptive Estimation in Practice
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    Chapter 13 Time Series Prediction via Aggregation: An Oracle Bound Including Numerical Cost
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    Chapter 14 Space-Time Trajectories of Wind Power Generation: Parametrized Precision Matrices Under a Gaussian Copula Approach
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    Chapter 15 Game-Theoretically Optimal Reconciliation of Contemporaneous Hierarchical Time Series Forecasts
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    Chapter 16 The BAGIDIS Distance: About a Fractal Topology, with Applications to Functional Classification and Prediction
Attention for Chapter 4: Constructing Graphical Models via the Focused Information Criterion
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Chapter title
Constructing Graphical Models via the Focused Information Criterion
Chapter number 4
Book title
Modeling and Stochastic Learning for Forecasting in High Dimensions
Published by
Springer, Cham, January 2015
DOI 10.1007/978-3-319-18732-7_4
Book ISBNs
978-3-31-918731-0, 978-3-31-918732-7
Authors

Gerda Claeskens, Eugen Pircalabelu, Lourens Waldorp

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 33%
Researcher 1 33%
Other 1 33%
Readers by discipline Count As %
Mathematics 1 33%
Psychology 1 33%
Materials Science 1 33%