Awan, U. ; Shamim, S. ; Khan, Z. Big data analytics capability and decision-making: the role of data-driven insight on circular economy performance[J]. 2021 Technol Forecast Soc Change. 168 -
Baltagi, B.H. ; Maasoumi, E. An overview of dependence in cross-section, time-series, and panel data[J]. 2013 Econometr Rev. 32 543-546
- Bashir, F. ; Wei, H.L. Handling missing data in multivariate time series using a vector autoregressive model-imputation (VAR-IM) algorithm[J]. 2018 Neurocomputing. 276 23-30
Paper not yet in RePEc: Add citation now
- Bradley, W. ; Kim, J. ; Kilwein, Z. Perspectives on the integration between first-principles and data-driven modeling[J]. 2022 Comput & Chem Eng. 166 -
Paper not yet in RePEc: Add citation now
- Chen, L. The theoretical system and institutional changes of China’s industrial statistics—concurrently discussing some systematic errors in China’s industrial enterprise data[J]. 2019 Econom Sci. 4 69-80
Paper not yet in RePEc: Add citation now
- Chi, J.T. ; Chi, E.C. ; Baraniuk, R.G. K-pod: a method for k-means clustering of missing data[J]. 2016 American Statist. 70 91-99
Paper not yet in RePEc: Add citation now
- Cui, Z. ; Ke, R. ; Pu, Z. Stacked bidirectional and unidirectional LSTM recurrent neural network for forecasting network-wide traffic state with missing values[J]. 2020 Transport Res Part C: Emerg Technol. 118 -
Paper not yet in RePEc: Add citation now
Dang, H.A. ; Jolliffe, D. ; Carletto, C. Data gaps, data incomparability, and data imputation: a review of poverty measurement methods for data-scarce environments[J]. 2019 J Econom Surv. 33 757-797
- Demirhan, H. ; Renwick, Z. Missing value imputation for short to mid-term horizontal solar irradiance data[J]. 2018 Appl Energy. 225 998-1012
Paper not yet in RePEc: Add citation now
- Doidge, J.C. Responsiveness-informed multiple imputation and inverse probability-weighting in cohort studies with missing data that are non-monotone or not missing at random[J]. 2018 Stat Methods Med Res. 27 352-363
Paper not yet in RePEc: Add citation now
- Faisal, S. ; Tutz, G. Nearest neighbor imputation for categorical data by weighting of attributes[J]. 2022 Inform Sci. 592 306-319
Paper not yet in RePEc: Add citation now
- Fan, F. ; Li, Z. ; Chen, Q. Relational data imputation with quality guarantee[J]. 2018 Inform Sci. 465 305-322
Paper not yet in RePEc: Add citation now
- Fan, J. ; Chow, T.W.S. ; Qin, S.J. Kernel-based statistical process monitoring and fault detection in the presence of missing data[J]. 2021 IEEE Trans Industr Inform. 18 4477-4487
Paper not yet in RePEc: Add citation now
- Gao, P. ; Wang, M. ; Chow, J.H. Missing data recovery for high-dimensional signals with nonlinear low-dimensional structures[J]. 2017 IEEE Trans Signal Process. 65 5421-5436
Paper not yet in RePEc: Add citation now
- Graham, J.W. Missing data analysis: making it work in the real world[J]. 2009 Annu Rev Psychol. 60 549-576
Paper not yet in RePEc: Add citation now
- Hadeed, S.J. ; O’Rourke, M.K. ; Burgess, J.L. Imputation methods for addressing missing data in short-term monitoring of air pollutants[J]. 2020 Sci Total Environ. 730 -
Paper not yet in RePEc: Add citation now
- Han, J. ; Kang, S. Dynamic imputation for improved training of neural network with missing values[J]. 2022 Expert Syst Applicat. 194 -
Paper not yet in RePEc: Add citation now
Holz, C.A. Monthly industrial output in China 1980–2012[J]. 2014 China Econom Rev. 28 1-16
- Hoyos-Gómez, L.S. ; Ruiz-Muñoz, J.F. ; Ruiz-Mendoza, B.J. Short-term forecasting of global solar irradiance in tropical environments with incomplete data[J]. 2022 Appl Energy. 307 -
Paper not yet in RePEc: Add citation now
- Hsiao, C.Y.L. ; Sheng, N. ; Fu, S. Evaluation of contagious effects of China’s wind power industrial policies[J]. 2022 Energy. 238 -
Paper not yet in RePEc: Add citation now
- Iantovics, L.B. ; Enăchescu, C. Method for data quality assessment of synthetic industrial data[J]. 2022 Sensors. 22 1608-
Paper not yet in RePEc: Add citation now
- Ispirova, G. ; Eftimov, T. ; Seljak, B.K. Evaluating missing value imputation methods for food composition databases[J]. 2020 Food Chem Toxicol. 141 -
Paper not yet in RePEc: Add citation now
- Janjarasjitt, S. ; Scher, M.S. ; Loparo, K.A. Nonlinear dynamical analysis of the neonatal EEG time series: the relationship between sleep state and complexity[J]. 2008 Clin Neurophysiol. 119 1812-1823
Paper not yet in RePEc: Add citation now
Jeong, D. ; Park, C. ; Ko, Y.M. Missing data imputation using mixture factor analysis for building electric load data[J]. 2021 Appl Energy. 304 -
Jing, X. ; Luo, J. ; Wang, J. A multi-imputation method to deal with hydro-meteorological missing values by integrating chain equations and random forest[J]. 2022 Water Res Manag. 36 1159-1173
Juárez, M.A. ; Steel, M.F.J. Model-based clustering of non-Gaussian panel data based on skew-t distributions[J]. 2010 J Business & Econom Statist. 28 52-66
- Junger, W.L. ; De Leon, A.P. Imputation of missing data in time series for air pollutants[J]. 2015 Atmos Environ. 102 96-104
Paper not yet in RePEc: Add citation now
- Karmitsa, N. ; Taheri, S. ; Bagirov, A. Missing value imputation via clusterwise linear regression[J]. 2020 IEEE Trans Knowl Data Eng. 34 1889-1901
Paper not yet in RePEc: Add citation now
- Kim, S. ; Choi, C.Y. ; Shahandashti, M. Improving accuracy in predicting city-level construction cost indices by combining linear ARIMA and nonlinear ANNs[J]. 2022 J Manag Eng. 38 04021093-
Paper not yet in RePEc: Add citation now
- Li, J. ; Chen, W. An improved grey clustering model with multiattribute spatial-temporal feature for panel data and its application[J]. 2020 Math Probl Eng. 2020 1-9
Paper not yet in RePEc: Add citation now
Liguori, A. ; Markovic, R. ; Ferrando, M. Augmenting energy time-series for data-efficient imputation of missing values[J]. 2023 Appl Energy. 334 -
- Little, R.J.A. ; Rubin, D.B. Statistical analysis with missing data[M]. 2019 John Wiley & Sons:
Paper not yet in RePEc: Add citation now
- Ma, J. ; Cheng, J.C.P. ; Jiang, F. A bi-directional missing data imputation scheme based on LSTM and transfer learning for building energy data[J]. 2020 Energ Buildings. 216 -
Paper not yet in RePEc: Add citation now
- Nakagawa, S. ; Freckleton, R.P. Missing inaction: the dangers of ignoring missing data[J]. 2008 Trends Ecol Evol. 23 592-596
Paper not yet in RePEc: Add citation now
- Nishanth, K.J. ; Ravi, V. ; Ankaiah, N. Soft computing based imputation and hybrid data and text mining: the case of predicting the severity of phishing alerts[J]. 2012 Expert Syst Applicat. 39 10583-10589
Paper not yet in RePEc: Add citation now
- Pan, Z. ; Wang, Y. ; Wang, K. Imputation of missing values in time series using an adaptive-learned median-filled deep autoencoder[J]. 2022 IEEE Transact Cybernet. 53 695-706
Paper not yet in RePEc: Add citation now
Peng, L. ; Zhang, Q. ; Yao, Z. Underreported coal in statistics: a survey-based solid fuel consumption and emission inventory for the rural residential sector in China[J]. 2019 Appl Energy. 235 1169-1182
- Razavi-Far, R. ; Cheng, B. ; Saif, M. Similarity-learning information-fusion schemes for missing data imputation[J]. 2020 Knowledge-Based Syst. 187 104805-
Paper not yet in RePEc: Add citation now
- Ren, L. ; Wang, T. ; Seklouli, A.S. A review on missing values for main challenges and methods[J]. 2023 Informat Syst. -
Paper not yet in RePEc: Add citation now
- Sefidian, A.M. ; Daneshpour, N. Missing value imputation using a novel grey based fuzzy c-means, mutual information based feature selection, and regression model[J]. 2019 Expert Syst Applicat. 115 68-94
Paper not yet in RePEc: Add citation now
- Sinton, J.E. Accuracy and reliability of China’s energy statistics[J]. 2001 China Econom Rev. 12 373-383
Paper not yet in RePEc: Add citation now
- Spiegler, R. “Data monkeys”: a procedural model of extrapolation from partial statistics[J]. 2017 Rev Econom Studi. 84 1818-1841
Paper not yet in RePEc: Add citation now
Tang, L. ; Yu, L. ; He, K. A novel data-characteristic-driven modeling methodology for nuclear energy consumption forecasting[J]. 2014 Appl Energy. 128 1-14
- Tencaliec, P. ; Favre, A.C. ; Prieur, C. Reconstruction of missing daily streamflow data using dynamic regression models[J]. 2015 Water Resour Res. 51 9447-9463
Paper not yet in RePEc: Add citation now
- Theiler, J. ; Eubank, S. ; Longtin, A. Testing for nonlinearity in time series: the method of surrogate data[J]. 1992 Phys D: Nonlinear Phenom. 58 77-94
Paper not yet in RePEc: Add citation now
- Tran, C.T. ; Zhang, M. ; Andreae, P. An effective and efficient approach to classification with incomplete data[J]. 2018 Knowledge-Based Syst. 154 1-16
Paper not yet in RePEc: Add citation now
Uebele, M. ; Ritschl, A. Stock markets and business cycle comovement in Germany before world war I: evidence from spectral analysis[J]. 2009 J Macroeconom. 31 35-57
Wang, D. ; Chen, F. ; Mao, J. Are the official national data credible? Empirical evidence from statistics quality evaluation of China’s coal and its downstream industries[J]. 2022 Energy Econ. 114 -
Wang, D. ; Tian, C. ; Mao, J. Forecasting coal demand in key coal consuming industries based on the data-characteristic-driven decomposition ensemble model[J]. 2023 Energy. 282 -
- Wang, X. ; Li, T. ; Ikhumhen, H.O. Spatio-temporal variability and persistence of PM2. 5 concentrations in China using trend analysis methods and Hurst exponent[J]. Atmospheric. 2022 Pollut Res. 13 -
Paper not yet in RePEc: Add citation now
- Xie, G. ; Zhang, N. ; Wang, S. Data characteristic analysis and model selection for container throughput forecasting within a decomposition-ensemble methodology[J]. 2017 Transport Res Part E: Logist Transportat Rev. 108 160-178
Paper not yet in RePEc: Add citation now
Yang, D. ; Guo, J. ; Sun, S. An interval decomposition-ensemble approach with data-characteristic-driven reconstruction for short-term load forecasting[J]. 2022 Appl Energy. 306 -
- Ye, C. ; Wang, H. ; Lu, W. Effective Bayesian-network-based missing value imputation enhanced by crowdsourcing[J]. 2020 Knowledge-Based Syst. 190 -
Paper not yet in RePEc: Add citation now
- Young, R. ; Johnson, D.R. Handling missing values in longitudinal panel data with multiple imputation[J]. 2015 J Marriage Fam. 77 277-294
Paper not yet in RePEc: Add citation now
- Yu, J. ; Yan, X. Data-feature-driven nonlinear process monitoring based on joint deep learning models with dual-scale[J]. 2022 Inform Sci. 591 381-399
Paper not yet in RePEc: Add citation now
Yu, L. ; Wang, Z. ; Tang, L. A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting[J]. 2015 Appl Energy. 156 251-267
- Zhang, Y.F. ; Thorburn, P.J. ; Xiang, W. SSIM—A deep learning approach for recovering missing time series sensor data[J]. 2019 IEEE Internet Things J. 6 6618-6628
Paper not yet in RePEc: Add citation now