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A novel ranking procedure for forecasting approaches using Data Envelopment Analysis
16 references·1 citing·32 second hop
A novel ranking procedure for forecasting approaches using Data Envelopment Analysis (2016)A novel ranking procedure for forecasting…Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts (2013)Measuring forecasting accurac…Data envelopment analysis (DEA) – Thirty years on (2008)Data envelopment analysis (DE…A modified super-efficiency DEA model for infeasibility (2008)A modified super-efficiency D…DEA models for ratio data: Convexity consideration (2007)DEA models for ratio data: Co…Another look at measures of forecast accuracy (2006)Another look at measures of f…25 years of time series forecasting (2006)25 years of time series forec…The accuracy of intermittent demand estimates (2004)The accuracy of intermittent …Use of ratios in data envelopment analysis (2003)Use of ratios in data envelop…Measuring super-efficiency in DEA in the presence of infeasibility (2003)Measuring super-efficiency in…Modeling undesirable factors in efficiency evaluation (2002)Modeling undesirable factors …The M3-Competition: results, conclusions and implications (2000)The M3-Competition: results, …Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis (1984)Some Models for Estimating Te…The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)The accuracy of extrapolation…A multiplicative model for efficiency analysis (1982)A multiplicative model for ef…Measuring the efficiency of decision making units (1978)Measuring the efficiency of d…Forecasting principles and practiceForecasting principles and pr…Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019) (2022)Quantitative modelling fronti…Multilateral Productivity Comparisons When Some Outputs are Undesirable: A Nonparametric Approach (1989)A survey of data envelopment analysis in energy and environmental studies (2007)Data envelopment analysis: Prior to choosing a model (2013)How does green finance affect green total factor productivity? Evidence from China (2022)The Measurement of Productive Efficiency (1957)Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey (2009)Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach (2012)STATE OF ART SURVEYS OF OVERVIEWS ON MCDM/MADM METHODS (2014)Combining forecasts: A review and annotated bibliography (1989)Forecasting and Stock Control for Intermittent Demands (1972)A Survey of Forecast Error Measures (2013)Supply chain forecasting: Theory, practice, their gap and the future (2015)Retail forecasting: Research and practice (2019)Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)On the use of cross-validation for time series predictor evaluation (2012)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Time series forecasting of petroleum production using deep LSTM recurrent networks (2018)The Combination of Forecasts (1969)Exponential smoothing: The state of the art (1985)Combining forecasts: A review and annotated bibliography (1990)Error measures for generalizing about forecasting methods: Empirical comparisons (1992)Forecasting methods and applications (1993)Automatic Time Series Forecasting: The forecast Package for R (2008)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)A Procedure for Ranking Efficient Units in Data Envelopment Analysis (1993)A slacks-based measure of efficiency in data envelopment analysis (2001)A slacks-based measure of super-efficiency in data envelopment analysis (2002)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)
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References

  • 1978Measuring the efficiency of decision making units29,755 cited
  • 1984Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis16,773 cited
  • 2006Another look at measures of forecast accuracy5,736 cited
  • n.d.Forecasting principles and practice4,364 cited
  • 2000The M3-Competition: results, conclusions and implications1,700 cited
  • 2008Data envelopment analysis (DEA) – Thirty years on1,603 cited
  • 200625 years of time series forecasting1,589 cited
  • 1982The accuracy of extrapolation (time series) methods: Results of a forecasting competition1,465 cited
  • 2002Modeling undesirable factors in efficiency evaluation1,461 cited
  • 2004The accuracy of intermittent demand estimates498 cited
  • 1982A multiplicative model for efficiency analysis295 cited
  • 2003Use of ratios in data envelopment analysis247 cited
  • 2007DEA models for ratio data: Convexity consideration210 cited
  • 2003Measuring super-efficiency in DEA in the presence of infeasibility198 cited
  • 2013Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts193 cited

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A modified super-efficiency DEA model for infeasibility
156 cited

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  • 2022Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)18 cited