1. Vers une désaisonnalisation des séries temporelles infra-mensuelles avec JDemetra+. (2024). Smyk, A ; Webel, K.
   In: Documents de Travail de l'Insee - INSEE Working Papers.
   RePEc:nse:doctra:m2024-04.

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2. Towards seasonal adjustment of infra-monthly time series with JDemetra+. (2023). Webel, Karsten ; Smyk, Anna.
   In: Discussion Papers.
   RePEc:zbw:bubdps:242023.

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3. An Improved Hybrid Approach for Daily Electricity Peak Demand Forecasting during Disrupted Situations: A Case Study of COVID-19 Impact in Thailand. (2023). Pannakkong, Warut ; Huynh, Van-Nam ; Aswanuwath, Lalitpat ; Buddhakulsomsiri, Jirachai ; Karnjana, Jessada.
   In: Energies.
   RePEc:gam:jeners:v:17:y:2023:i:1:p:78-:d:1305656.

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4. Enhancing Energy System Models Using Better Load Forecasts. (2023). Mobius, Thomas ; Grothe, Oliver ; Watermeyer, Mira ; Musgens, Felix.
   In: Papers.
   RePEc:arx:papers:2302.11017.

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5. A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series. (2022). Webel, Karsten.
   In: Discussion Papers.
   RePEc:zbw:bubdps:312022.

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6. A proposal for measuring and comparing seasonal variations in hourly economic time series. (2022). Cáceres-Hernández, José Juan ; Caceres-Hernandez, Jose Juan ; Hernandez-Martin, Jonay ; Martin-Rodriguez, Gloria.
   In: Empirical Economics.
   RePEc:spr:empeco:v:62:y:2022:i:4:d:10.1007_s00181-021-02079-3.

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7. A Bayesian Model to Forecast the Time Series Kinetic Energy Data for a Power System. (2021). Gonzalez-Longatt, Francisco ; Ghimire, Bishal ; Shrestha, Ashish.
   In: Energies.
   RePEc:gam:jeners:v:14:y:2021:i:11:p:3299-:d:568983.

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8. One-day-ahead electricity demand forecasting in holidays using discrete-interval moving seasonalities. (2021). Trull, Oscar ; Garcia-Diaz, Carlos J ; Troncoso, Alicia.
   In: Energy.
   RePEc:eee:energy:v:231:y:2021:i:c:s0360544221012147.

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9. Residual electricity demand: An empirical investigation. (2021). Molnár, Peter ; Lyócsa, Štefan ; Lyocsa, Tefan ; Molnar, Peter ; Catherine, Linh Phuong.
   In: Applied Energy.
   RePEc:eee:appene:v:283:y:2021:i:c:s0306261920316846.

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10. Use of Available Daylight to Improve Short-Term Load Forecasting Accuracy. (2020). Valero, Sergio ; Lopez, Miguel ; Senabre, Carolina ; Sans, Carlos.
    In: Energies.
    RePEc:gam:jeners:v:14:y:2020:i:1:p:95-:d:468767.

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11. Point and Interval Forecasting of Zonal Electricity Prices and Demand Using Heteroscedastic Models: The IPEX Case. (2020). Bernardi, Mauro ; Lisi, Francesco.
    In: Energies.
    RePEc:gam:jeners:v:13:y:2020:i:23:p:6191-:d:450862.

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12. Short-Term Load Forecasting for Spanish Insular Electric Systems. (2020). Juan, Jesus ; Caro, Eduardo.
    In: Energies.
    RePEc:gam:jeners:v:13:y:2020:i:14:p:3645-:d:384861.

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13. Daily retail demand forecasting using machine learning with emphasis on calendric special days. (2020). Huber, Jakob ; Stuckenschmidt, Heiner.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:36:y:2020:i:4:p:1420-1438.

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14. Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts. (2020). Ahmad, Tanveer ; Zhang, Hongcai.
    In: Energy.
    RePEc:eee:energy:v:209:y:2020:i:c:s0360544220315851.

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15. Daylight effect on the electricity demand in Spain and assessment of Daylight Saving Time policies. (2020). Lopez, Miguel.
    In: Energy Policy.
    RePEc:eee:enepol:v:140:y:2020:i:c:s0301421520301725.

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16. Electricity Forecasting Improvement in a Destination Using Tourism Indicators. (2019). Trull, Oscar ; Garcia-Diaz, Carlos J ; Peiro-Signes, Angel.
    In: Sustainability.
    RePEc:gam:jsusta:v:11:y:2019:i:13:p:3656-:d:245253.

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17. Classification of Special Days in Short-Term Load Forecasting: The Spanish Case Study. (2019). Valero, Sergio ; Lopez, Miguel ; Senabre, Carolina ; Sans, Carlos.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:7:p:1253-:d:219047.

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18. Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter. (2019). Trull, Oscar ; Garcia-Diaz, Carlos J ; Troncoso, Alicia.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:6:p:1083-:d:215824.

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19. On the Influence of Renewable Energy Sources in Electricity Price Forecasting in the Iberian Market. (2019). Lemus-Zuiga, Lenin G ; Iranzo-Sanchez, Javier ; Urchueguia, Javier F ; Onaindia, Eva ; Aineto, Diego.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:11:p:2082-:d:235959.

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20. A data-driven framework for predicting weather impact on high-volume low-margin retail products. (2019). Verstraete, Gylian ; Aghezzaf, El-Houssaine ; Desmet, Bram.
    In: Journal of Retailing and Consumer Services.
    RePEc:eee:joreco:v:48:y:2019:i:c:p:169-177.

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21. Empirical Comparison of Neural Network and Auto-Regressive Models in Short-Term Load Forecasting. (2018). Valero, Sergio ; Lopez, Miguel ; Senabre, Carolina ; Sans, Carlos.
    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:8:p:2080-:d:163007.

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22. A Practical Formulation for Ex-Ante Scheduling of Energy and Reserve in Renewable-Dominated Power Systems: Case Study of the Iberian Peninsula. (2018). Dominguez, Ruth ; Zarate-Miano, Rafael ; Carrion, Miguel.
    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:8:p:1939-:d:159981.

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23. Rule-based autoregressive moving average models for forecasting load on special days: A case study for France. (2018). Arora, Siddharth ; Taylor, James W.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:266:y:2018:i:1:p:259-268.

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24. Short-run electricity load forecasting with combinations of stationary wavelet transforms. (2018). Fouquau, Julien ; Bessec, Marie.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:264:y:2018:i:1:p:149-164.

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25. Functional Autoregressive Models: An Application to Brazilian Hourly Electricity Load. (2017). Vaz, Lucelia Viviane ; da Silveira, Getulio Borges.
    In: Brazilian Review of Econometrics.
    RePEc:sbe:breart:v:37:y:2017:i:2:a:62293.

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26. Demand for electricity and weather conditions: Nonparametric analysis. (2017). Shenkman, Evgeniya ; Ozhegov, Evgeniy ; Popova, Evgeniya.
    In: Applied Econometrics.
    RePEc:ris:apltrx:0317.

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27. A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting. (2017). Shao, Zhen ; Yang, Shan-Lin ; Zhou, Kai-Le ; Chao, FU.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:75:y:2017:i:c:p:123-136.

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28. Modelling weather effects for impact analysis of residential time-of-use electricity pricing. (2017). Miller, Reid ; Golab, Lukasz ; Rosenberg, Catherine.
    In: Energy Policy.
    RePEc:eee:enepol:v:105:y:2017:i:c:p:534-546.

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29. Forecasting quantiles of day-ahead electricity load. (2017). Hurn, Stan ; Clements, Adam ; Li, Z.
    In: Energy Economics.
    RePEc:eee:eneeco:v:67:y:2017:i:c:p:60-71.

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30. Collateral effects of liberalisation: Metering, losses, load profiles and cost settlement in Spain’s electricity system. (2016). Trujillo-Baute, Elisa ; Costa-Campi, Maria ; Batalla-Bejerano, Joan.
    In: Energy Policy.
    RePEc:eee:enepol:v:94:y:2016:i:c:p:421-431.

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31. Forecasting day-ahead electricity load using a multiple equation time series approach. (2016). Hurn, Stan ; Clements, Adam ; Li, Z.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:251:y:2016:i:2:p:522-530.

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32. Electricity consumption modelling: A case of Germany. (2016). Molnár, Peter ; Molnar, Peter ; Catherine, Linh Phuong ; Lin, Kuan-Heng.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:55:y:2016:i:c:p:92-101.

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33. Heat wave, electricity rationing, and trade-offs between environmental gains and economic losses: The example of Shanghai. (2016). Tian, Zhan ; Liu, Xiaochen ; Gu, Tingting ; Sun, Laixiang ; Feng, Kuishuang ; Zhong, Honglin ; Liang, Zhuoran.
    In: Applied Energy.
    RePEc:eee:appene:v:184:y:2016:i:c:p:951-959.

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34. Multiple seasonal cycles forecasting model: the Italian electricity demand. (2015). Petrella, Lea ; Bernardi, Mauro.
    In: Statistical Methods & Applications.
    RePEc:spr:stmapp:v:24:y:2015:i:4:p:671-695.

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35. Forecasting day-ahead electricity load using a multiple equation time series approach. (2015). Hurn, Stan ; Clements, Adam ; Li, Zili.
    In: NCER Working Paper Series.
    RePEc:qut:auncer:2015_01.

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36. Efficient modeling and forecasting of electricity spot prices. (2015). Husmann, Sven ; Steinert, Rick ; Ziel, Florian.
    In: Energy Economics.
    RePEc:eee:eneeco:v:47:y:2015:i:c:p:98-111.

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37. Forecasting day-ahead electricity load using a multiple equation time series approach. (2014). A. S Hurn, ; A. E Clements, .
    In: NCER Working Paper Series.
    RePEc:qut:auncer:wp103.

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38. Efficient Modeling and Forecasting of the Electricity Spot Price. (2014). Steinert, Rick ; Ziel, Florian.
    In: Papers.
    RePEc:arx:papers:1402.7027.

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39. Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings. (2013). Penya, Yoseba K. ; Bretos, Oscar ; Prieto, Juan ; Fernandez, Ivan ; Borges, Cruz E..
    In: Energies.
    RePEc:gam:jeners:v:6:y:2013:i:4:p:2110-2129:d:25082.

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40. Modeling special-day effects for forecasting intraday electricity demand. (2013). Kim, Myung Suk.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:230:y:2013:i:1:p:170-180.

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41. The power of weather. (2012). Zhou, Chen ; Ravazzolo, Francesco ; Huurman, Christian .
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:56:y:2012:i:11:p:3793-3807.

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42. Inflation forecasting in Angola: a fractional approach. (2012). Gil-Alana, Luis ; Barros, Carlos P..
    In: CEsA Working Papers.
    RePEc:cav:cavwpp:wp103.

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43. Estimation of tourism-induced electricity consumption: The case study of Balearics Islands, Spain. (2011). Rossello, Jaume ; Bakhat, Mohcine.
    In: Energy Economics.
    RePEc:eee:eneeco:v:33:y:2011:i:3:p:437-444.

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44. Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models. (2010). Nabney, Ian T. ; Nguyen, Hang T..
    In: Energy.
    RePEc:eee:energy:v:35:y:2010:i:9:p:3674-3685.

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45. Triple seasonal methods for short-term electricity demand forecasting. (2010). Taylor, James W..
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:204:y:2010:i:1:p:139-152.

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46. Forecasting electricity demand in Japan: A Bayesian spatial autoregressive ARMA approach. (2010). Ohtsuka, Yoshihiro ; Oga, Takashi ; Kakamu, Kazuhiko.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:54:y:2010:i:11:p:2721-2735.

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47. Factors affecting electricity demand in Athens, Greece and London, UK: A comparative assessment. (2009). Majithia, S. ; Petrakis, M. ; Giannakopoulos, C. ; Psiloglou, B. E..
    In: Energy.
    RePEc:eee:energy:v:34:y:2009:i:11:p:1855-1863.

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48. Frequency domain methods applied to forecasting electricity markets. (2009). Trapero, Juan R. ; Pedregal, Diego J..
    In: Energy Economics.
    RePEc:eee:eneeco:v:31:y:2009:i:5:p:727-735.

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49. A nonlinear mixed effects model for the prediction of natural gas consumption by individual customers. (2008). Konar, Ondrej ; Mal, Marek ; Brabec, Marek ; Pelikan, Emil.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:659-678.

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50. An evaluation of methods for very short-term load forecasting using minute-by-minute British data. (2008). Taylor, James W..
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:645-658.

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51. Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data. (2008). Medeiros, Marcelo ; Soares, Lacir J..
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:630-644.

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52. Input space to neural network based load forecasters. (2008). Ferreira, Vitor H. ; Velasquez, Roberto M. G., ; Alves da Silva, Alexandre P., .
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:616-629.

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18. Functional Autoregressive Models: An Application to Brazilian Hourly Electricity Load. (2017). Vaz, Lucelia Viviane ; da Silveira, Getulio Borges.
    In: Brazilian Review of Econometrics.
    RePEc:sbe:breart:v:37:y:2017:i:2:a:62293.

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19. Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs. (2017). Asfour, Shihab ; Buitrago, Jaime .
    In: Energies.
    RePEc:gam:jeners:v:10:y:2017:i:1:p:40-:d:86695.

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20. A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting. (2017). Shao, Zhen ; Yang, Shan-Lin ; Zhou, Kai-Le ; Chao, FU.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:75:y:2017:i:c:p:123-136.

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21. Modeling energy demand: Some emerging issues. (2016). Salisu, Afees ; AYINDE, Taofeek.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:54:y:2016:i:c:p:1470-1480.

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22. Forecasting day-ahead electricity load using a multiple equation time series approach. (2016). Hurn, Stan ; Clements, Adam ; Li, Z.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:251:y:2016:i:2:p:522-530.

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23. Construction of an informative hierarchical prior for a small sample with the help of historical data and application to electricity load forecasting. (2015). Launay, Tristan ; Lamarche, Sophie ; Philippe, Anne.
    In: TEST: An Official Journal of the Spanish Society of Statistics and Operations Research.
    RePEc:spr:testjl:v:24:y:2015:i:2:p:361-385.

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24. Forecasting day-ahead electricity load using a multiple equation time series approach. (2015). Hurn, Stan ; Clements, Adam ; Li, Zili.
    In: NCER Working Paper Series.
    RePEc:qut:auncer:2015_01.

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25. Forecasting generalized quantiles of electricity demand: A functional data approach. (2014). Schulz, Franziska ; López Cabrera, Brenda.
    In: SFB 649 Discussion Papers.
    RePEc:zbw:sfb649:sfb649dp2014-030.

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26. Forecasting day-ahead electricity load using a multiple equation time series approach. (2014). A. S Hurn, ; A. E Clements, .
    In: NCER Working Paper Series.
    RePEc:qut:auncer:wp103.

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27. Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach. (2014). Schulz, Franziska ; López Cabrera, Brenda.
    In: SFB 649 Discussion Papers.
    RePEc:hum:wpaper:sfb649dp2014-030.

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28. A SARIMAX coupled modelling applied to individual load curves intraday forecasting. (2013). Bercu, Sophie ; Frederic Proïa, .
    In: Journal of Applied Statistics.
    RePEc:taf:japsta:v:40:y:2013:i:6:p:1333-1348.

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29. Modeling and forecasting daily electricity load curves: a hybrid approach. (2013). Goude, Yannig ; Brossat, Xavier ; Yao, Qiwei ; Cho, Haeran.
    In: LSE Research Online Documents on Economics.
    RePEc:ehl:lserod:49634.

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30. A comparison of periodic autoregressive and dynamic factor models in intraday energy demand forecasting. (2013). Smith, Michael ; Mestekemper, Thomas ; Kauermann, Goran.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:29:y:2013:i:1:p:1-12.

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31. Modeling special-day effects for forecasting intraday electricity demand. (2013). Kim, Myung Suk.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:230:y:2013:i:1:p:170-180.

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32. Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing. (2012). Snyder, Ralph ; Taylor, James W..
    In: Omega.
    RePEc:eee:jomega:v:40:y:2012:i:6:p:748-757.

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33. Dynamic factors in periodic time-varying regressions with an application to hourly electricity load modelling. (2012). Ooms, Marius ; Koopman, Siem Jan ; Dordonnat, Virginie .
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:56:y:2012:i:11:p:3134-3152.

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34. A Survey on the Spanish Electricity Intraday Market/El mercado de electricidad español: el mercado intradiario. (2011). Furi, Dolores.
    In: Estudios de Economia Aplicada.
    RePEc:lrk:eeaart:29_2_13.

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35. Bicycle commuting in Melbourne during the 2000s energy crisis: A semiparametric analysis of intraday volumes. (2011). Smith, Michael ; Kauermann, Gran.
    In: Transportation Research Part B: Methodological.
    RePEc:eee:transb:v:45:y:2011:i:10:p:1846-1862.

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36. A heuristic method for parameter selection in LS-SVM: Application to time series prediction. (2011). Herrera, Luis Javier ; Rojas, Ignacio ; Pomares, Hector ; Rubio, Gines .
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:27:y::i:3:p:725-739.

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37. Estimation of tourism-induced electricity consumption: The case study of Balearics Islands, Spain. (2011). Rossello, Jaume ; Bakhat, Mohcine.
    In: Energy Economics.
    RePEc:eee:eneeco:v:33:y:2011:i:3:p:437-444.

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38. Functional clustering and linear regression for peak load forecasting. (2010). Fusai, Gianluca ; May, Caterina ; Goia, Aldo.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:26:y::i:4:p:700-711.

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39. Functional hourly forecasting of water temperature. (2010). Mestekemper, Thomas ; Windmann, Michael ; Kauermann, Goran.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:26:y::i:4:p:684-699.

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40. Bayesian skew selection for multivariate models. (2010). Smith, Michael ; Panagiotelis, Anastasios.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:54:y:2010:i:7:p:1824-1839.

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41. Forecasting electricity demand in Japan: A Bayesian spatial autoregressive ARMA approach. (2010). Ohtsuka, Yoshihiro ; Oga, Takashi ; Kakamu, Kazuhiko.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:54:y:2010:i:11:p:2721-2735.

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42. A new approach to estimating tourism-induced electricity consumption. (2009). Rossello, Jaume ; Bakhat, Mohcine ; Nadal, Jaume Rossello.
    In: CRE Working Papers (Documents de treball del CRE).
    RePEc:pdm:wpaper:2009/6.

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43. An Hourly Periodic State Space Model for Modelling French National Electricity Load. (2008). Ooms, Marius ; Koopman, Siem Jan ; Collet, J. ; Dessertaine, A. ; Dordonnat, V..
    In: Tinbergen Institute Discussion Papers.
    RePEc:tin:wpaper:20080008.

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44. Interday Forecasting and Intraday Updating of Call Center Arrivals. (2008). Huang, Jianhua Z. ; Shen, Haipeng.
    In: Manufacturing & Service Operations Management.
    RePEc:inm:ormsom:v:10:y:2008:i:3:p:391-410.

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45. Bayesian density forecasting of intraday electricity prices using multivariate skew t distributions. (2008). Smith, Michael ; Panagiotelis, Anastasios.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:710-727.

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46. A nonlinear mixed effects model for the prediction of natural gas consumption by individual customers. (2008). Konar, Ondrej ; Mal, Marek ; Brabec, Marek ; Pelikan, Emil.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:659-678.

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47. An evaluation of methods for very short-term load forecasting using minute-by-minute British data. (2008). Taylor, James W..
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:645-658.

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48. Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data. (2008). Medeiros, Marcelo ; Soares, Lacir J..
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:630-644.

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49. Forecasting the electricity load from one day to one week ahead for the Spanish system operator. (2008). Espasa, Antoni ; Grafe, Rosmarie ; Cancelo, Jose Ramon.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:588-602.

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50. An hourly periodic state space model for modelling French national electricity load. (2008). Ooms, Marius ; Koopman, Siem Jan ; Dordonnat, V. ; Collet, J. ; Dessertaine, A..
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:4:p:566-587.

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51. Forecasting time series with multiple seasonal patterns. (2008). Vahid, Farshid ; Snyder, Ralph ; Ord, John ; Hyndman, Rob ; Gould, Phillip G. ; Koehler, Anne B..
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:191:y:2008:i:1:p:207-222.

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52. Bayesian identification, selection and estimation of semiparametric functions in high-dimensional additive models. (2008). Smith, Michael ; Panagiotelis, Anastasios.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:143:y:2008:i:2:p:291-316.

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53. Seasonal dynamic factor analysis and bootstrap inference : application to electricity market forecasting. (2008). Sanchez, Maria Jesus ; Rodriguez, Julio ; Garcia-Martos, Carolina ; Alonso, Andres M..
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:ws081406.

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54. Short Term Demand Forecasting Using Double Exponential Smoothing and Interventions to Account for Holidays and Temperature Effects. (2007). Souza, Reinaldo Castro ; Barros, Monica ; Cristina Vidigal Cabral de Miranda, .
    In: EcoMod2007.
    RePEc:ekd:000239:23900058.

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55. Forecasting from one day to one week ahead for the Spanish system operator. (2007). Espasa, Antoni ; Grafe, Rosemarie ; Cancelo, Jose Ramon.
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:ws078418.

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56. A semi-parametric time series approach in modeling hourly electricity loads. (2006). Chen, Rong ; Liu, Lon-Mu ; Harris, John L..
    In: Journal of Forecasting.
    RePEc:jof:jforec:v:25:y:2006:i:8:p:537-559.

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57. Modelling and forecasting short-term electricity load: a two step methodology. (2005). Medeiros, Marcelo ; Soares, Lacir J..
    In: Textos para discussão.
    RePEc:rio:texdis:495.

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58. Forecasting Time-Series with Correlated Seasonality. (2005). Vahid, Farshid ; Snyder, Ralph ; Ord, John ; Hyndman, Rob ; Gould, Phillip ; Koehler, Anne B..
    In: Monash Econometrics and Business Statistics Working Papers.
    RePEc:msh:ebswps:2004-28.

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59. Temperature and seasonality influences on Spanish electricity load. (2002). Meneu, Vicente ; Valor, Enric ; Pardo, Angel.
    In: Energy Economics.
    RePEc:eee:eneeco:v:24:y:2002:i:1:p:55-70.

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60. TESTING FOR WEEKLY SEASONAL UNIT ROOTS IN DAILY ELECTRICITY DEMAND: EVIDENCE FROM DEREGULATED MARKETS. (2001). Rubia, Antonio.
    In: Working Papers. Serie EC.
    RePEc:ivi:wpasec:2001-21.

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