A novel data-characteristic-driven modeling approach for imputing missing value in industrial statistics: A case study of China electricity statistics
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DOI: 10.1016/j.apenergy.2024.123854
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- Hai‐Anh Dang & Dean Jolliffe & Calogero Carletto, 2019.
"Data Gaps, Data Incomparability, And Data Imputation: A Review Of Poverty Measurement Methods For Data‐Scarce Environments,"
Journal of Economic Surveys, Wiley Blackwell, vol. 33(3), pages 757-797, July.
- Dang,Hai-Anh H. & Jolliffe,Dean Mitchell & Carletto,Calogero & Dang,Hai-Anh H. & Jolliffe,Dean Mitchell & Carletto,Calogero, 2017. "Data gaps, data incomparability, and data imputation : a review of poverty measurement methods for data-scarce environments," Policy Research Working Paper Series 8282, The World Bank.
- Dang, Hai-Anh & Jolliffe, Dean & Carletto, Calogero, 2018. "Data Gaps, Data Incomparability, and Data Imputation: A Review of Poverty Measurement Methods for Data-Scarce Environments," GLO Discussion Paper Series 179, Global Labor Organization (GLO).
- Hai-Anh Dang & Dean Jolliffe & Calogero Carletto, 2018. "Data gaps, data incomparability, and data imputation: A review of poverty measurement methods for data-scarce environments," Working Papers 456, ECINEQ, Society for the Study of Economic Inequality.
- Juárez, Miguel A. & Steel, Mark F. J., 2010. "Model-Based Clustering of Non-Gaussian Panel Data Based on Skew-t Distributions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 52-66.
- Yu, Lean & Wang, Zishu & Tang, Ling, 2015. "A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting," Applied Energy, Elsevier, vol. 156(C), pages 251-267.
- Uebele, Martin & Ritschl, Albrecht, 2009.
"Stock markets and business cycle comovement in Germany before World War I: Evidence from spectral analysis,"
Journal of Macroeconomics, Elsevier, vol. 31(1), pages 35-57, March.
- Ritschl, Albrecht & Uebele, Martin, 2005. "Stock markets and business cvycle comovement in Germany before World War I: Evidence from spectral analysis," SFB 649 Discussion Papers 2005-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Ritschl, Albrecht & Uebele, Martin, 2005. "Stock Markets and Business Cycle Comovement in Germany Before World War I: Evidence from Spectral Analysis," CEPR Discussion Papers 5370, C.E.P.R. Discussion Papers.
- Wang, Delu & Tian, Cuicui & Mao, Jinqi & Chen, Fan, 2023. "Forecasting coal demand in key coal consuming industries based on the data-characteristic-driven decomposition ensemble model," Energy, Elsevier, vol. 282(C).
- Wang, Delu & Chen, Fan & Mao, Jinqi & Liu, Nannan & Rong, Fangyu, 2022. "Are the official national data credible? Empirical evidence from statistics quality evaluation of China's coal and its downstream industries," Energy Economics, Elsevier, vol. 114(C).
- Holz, Carsten A., 2014. "Monthly industrial output in China 1980–2012," China Economic Review, Elsevier, vol. 28(C), pages 1-16.
- Peng, Liqun & Zhang, Qiang & Yao, Zhiliang & Mauzerall, Denise L. & Kang, Sicong & Du, Zhenyu & Zheng, Yixuan & Xue, Tao & He, Kebin, 2019. "Underreported coal in statistics: A survey-based solid fuel consumption and emission inventory for the rural residential sector in China," Applied Energy, Elsevier, vol. 235(C), pages 1169-1182.
- Jeong, Dongyeon & Park, Chiwoo & Ko, Young Myoung, 2021. "Missing data imputation using mixture factor analysis for building electric load data," Applied Energy, Elsevier, vol. 304(C).
- Badi H. Baltagi & Esfandiar Maasoumi, 2013. "An Overview of Dependence in Cross-Section, Time-Series, and Panel Data," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 543-546, August.
- Tang, Ling & Yu, Lean & He, Kaijian, 2014. "A novel data-characteristic-driven modeling methodology for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 128(C), pages 1-14.
- Liguori, Antonio & Markovic, Romana & Ferrando, Martina & Frisch, Jérôme & Causone, Francesco & van Treeck, Christoph, 2023. "Augmenting energy time-series for data-efficient imputation of missing values," Applied Energy, Elsevier, vol. 334(C).
- Xin Jing & Jungang Luo & Jingmin Wang & Ganggang Zuo & Na Wei, 2022. "A Multi-imputation Method to Deal With Hydro-Meteorological Missing Values by Integrating Chain Equations and Random Forest," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1159-1173, March.
- Yang, Dongchuan & Guo, Ju-e & Sun, Shaolong & Han, Jing & Wang, Shouyang, 2022. "An interval decomposition-ensemble approach with data-characteristic-driven reconstruction for short-term load forecasting," Applied Energy, Elsevier, vol. 306(PA).
- Awan, Usama & Shamim, Saqib & Khan, Zaheer & Zia, Najam Ul & Shariq, Syed Muhammad & Khan, Muhammad Naveed, 2021. "Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
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Keywords
Industrial statistics; Missing value; Data imputation; Data-characteristic-driven; Modeling approach;All these keywords.
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