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Details about Bartosz Uniejewski

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Workplace:Katedra Badań Operacyjnych i Inteligencji Biznesowej (Department of Operations Research and Business Intelligence), Politechnika Wrocławska (Wroclaw University of Science and Technology), (more information at EDIRC)

Access statistics for papers by Bartosz Uniejewski.

Last updated 2020-02-26. Update your information in the RePEc Author Service.

Short-id: pun47


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Working Papers

2020

  1. Beating the naive: Combining LASSO with naive intraday electricity price forecasts
    WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology Downloads
  2. PCA forecast averaging - predicting day-ahead and intraday electricity prices
    WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology Downloads

2019

  1. Regularized Quantile Regression Averaging for probabilistic electricity price forecasting
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology Downloads

2018

  1. Efficient forecasting of electricity spot prices with expert and LASSO models
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology Downloads View citations (9)
    See also Journal Article in Energies (2018)
  2. Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology Downloads View citations (2)
  3. Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology Downloads View citations (4)
    See also Journal Article in International Journal of Forecasting (2019)

2017

  1. Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology Downloads View citations (11)
  2. On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology Downloads View citations (15)
    See also Journal Article in Energy Economics (2019)
  3. Variance stabilizing transformations for electricity spot price forecasting
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology Downloads View citations (17)

2016

  1. Automated variable selection and shrinkage for day-ahead electricity price forecasting
    HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology Downloads View citations (33)
    See also Journal Article in Energies (2016)

Journal Articles

2019

  1. Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting
    Energies, 2019, 12, (13), 1-12 Downloads View citations (5)
  2. On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks
    International Journal of Forecasting, 2019, 35, (4), 1520-1532 Downloads View citations (1)
  3. On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II — Probabilistic forecasting
    Energy Economics, 2019, 79, (C), 171-182 Downloads View citations (4)
    See also Working Paper (2017)
  4. Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO
    International Journal of Forecasting, 2019, 35, (4), 1533-1547 Downloads View citations (10)
    See also Working Paper (2018)

2018

  1. Efficient Forecasting of Electricity Spot Prices with Expert and LASSO Models
    Energies, 2018, 11, (8), 1-26 Downloads View citations (12)
    See also Working Paper (2018)

2016

  1. Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting
    Energies, 2016, 9, (8), 1-22 Downloads View citations (33)
    See also Working Paper (2016)

Software Items

2018

  1. ENERGIES_9_621_CODES: MATLAB codes for computing electricity spot price forecasts from "Automated variable selection and shrinkage for day-ahead electricity price forecasting"
    HSC Software, Hugo Steinhaus Center, Wroclaw University of Technology Downloads
  2. ENERGIES_9_621_FIGS: MATLAB codes and data for plotting figures from "Automated variable selection and shrinkage for day-ahead electricity price forecasting"
    HSC Software, Hugo Steinhaus Center, Wroclaw University of Technology Downloads
 
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