Modeling and Stochastic Learning for Forecasting in High Dimensions

No abstract is available for this paper.

• Publication year

  2015

• Venue

  Unknown venue

• Publication date

  2015-06-05

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1007/978-3-319-18732-7_3
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Generalized additive models for large data sets

  2015cited by this paper
• GEFCom2012: Electric load forecasting and backcasting with semi-parametric models

  2014cited by this paper
• Modeling and Forecasting Daily Electricity Load Curves: A Hybrid Approach

  2013influential reference
• Dynamic factors in periodic time-varying regressions with an application to hourly electricity load modelling

  2012cited by this paper
• Short-Term Load Forecasting Based on a Semi-Parametric Additive Model

  2012cited by this paper
• Forecasting electricity consumption by aggregating specialized experts

  2012cited by this paper
• Factor modeling for high-dimensional time series: inference for the number of factors

  2012cited by this paper
• Prévision non paramétrique de processus à valeurs fonctionnelles : application à la consommation d’électricité

  2011cited by this paper
• Functional linear regression via canonical analysis

  2010cited by this paper
• Identifying the finite dimensionality of curve time series

  2010cited by this paper
• Functional Clustering using Wavelets

  2010cited by this paper
• Clustering Functional Data using Wavelets

  2010cited by this paper
• An Hourly Periodic State Space Model for Modelling French National Electricity Load

  2008cited by this paper
• Methodology and convergence rates for functional linear regression

  2007cited by this paper
• Functional clustering and identifying substructures of longitudinal data

  2007cited by this paper
• Determining the Number of Factors in the General Dynamic Factor Model

  2007cited by this paper
• The Adaptive Lasso and Its Oracle Properties

  2006cited by this paper
• Functional clustering by Bayesian wavelet methods

  2006cited by this paper
• Assessing the finite dimensionality of functional data

  2006cited by this paper
• Functional linear regression analysis for longitudinal data

  2005cited by this paper
• A NON-LINEAR REGRESSION MODEL FOR MID-TERM LOAD FORECASTING AND IMPROVEMENTS IN SEASONALITY

  2005cited by this paper
• CATS

  2005cited by this paper
• Addendum: Regularization and variable selection via the elastic net

  2005cited by this paper
• Clustering for Sparsely Sampled Functional Data

  2003cited by this paper
• Ridge Regression: Biased Estimation for Nonorthogonal Problems

  2000cited by this paper
• Linear Processes in Function Spaces: Theory And Applications

  2000cited by this paper
• Regression Shrinkage and Selection via the Lasso

  1996cited by this paper
• Some Tools for Functional Data Analysis

  1991cited by this paper
• Ridge Regression: Applications to Nonorthogonal Problems

  1970cited by this paper
• The Eigen‐Values and Singular Values of Integral Equations†

  1938cited by this paper

• Modeling Daily Load Curve Parameters for a University under Prevailing Power Supply Conditions in Nigeria’s Local Grids Using Probabilistic Statistics

  2024cites this paper
• Concentration inequalities for non-causal random fields

  2022cites this paper
• Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting

  2022cites this paper
• Method for Determining the Optimal Capacity of Energy Storage Systems with a Long-Term Forecast of Power Consumption

  2021cites this paper
• Smart4RES Identification of new and enhanced forecasting products

  2021cites this paper
• Hydrometeorological evaluation of two nowcasting systems for Mediterranean heavy precipitation events with operational considerations

  2020cites this paper
• Generalized Network Autoregressive Processes and the GNAR Package

  2020cites this paper
• Adaptive Methods for Short-Term Electricity Load Forecasting During COVID-19 Lockdown in France

  2020cites this paper
• Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression

  2020cites this paper
• Generating Residential PV Production and Electricity Consumption Scenarios via Generative Adversarial Networks

  2019cites this paper
• Log-linear models independence structure comparison

  2019cites this paper
• Generalised Network Autoregressive Processes and the GNAR package

  2019cites this paper
• Short-term Load Forecasting : A Case Study in Chongqing Factories

  2019cites this paper
• Efficient Comparison Of Independence Structures Of Log-Linear Models

  2019cites this paper
• Nonparametric Bayesian volatility learning under microstructure noise

  2018cites this paper
• Exponential inequalities for nonstationary Markov chains

  2018cites this paper
• CVaR-based energy management scheme for optimal resilience and operational cost in commercial building microgrids

  2018cites this paper
• Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry

  2017influential citation
• Electricity Forecasting Using Multi-Stage Estimators of Nonlinear Additive Models

  2016cites this paper
• Blankets Joint Posterior score for learning Markov network structures

  2016cites this paper
• Self-tuning for cloud database clusters

  2016cites this paper
• Modelling, Detrending and Decorrelation of Network Time Series

  2016influential citation
• Mean shift densification of scarce data sets in short-term electric power load forecasting for special days

  2016cites this paper
• Estratégia para predição de consumo de energia elétrica de curto prazo: uma abordagem baseada em densificação com MEAN SHIFT para tratamento de dias especiais

  2016cites this paper
• Forecasting Electricity Consumption by Aggregating Experts; How to Design a Good Set of Experts

  2015cites this paper
• Smart4RES Identification of new forecasting products

  year unknowncites this paper