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Another look at forecast selection and combination: Evidence from forecast pooling
16 references·14 citing·22 second hop
Another look at forecast selection and combination: Evidence from forecast pooling (2018)Another look at forecast selection and co…forecast: Forecasting Functions for Time Series and Linear Models (2009)forecast: Forecasting Functio…Forecasting with Exponential Smoothing : The State Space Approach (2008)Forecasting with Exponential …Exponential smoothing: The state of the art—Part II (2006)Exponential smoothing: The st…Combination forecasts of output growth in a seven‐country data set (2004)Combination forecasts of outp…A state space framework for automatic forecasting using exponential smoothing methods (2002)A state space framework for a…Time-Series Forecasting (2000)Time-Series ForecastingThe M3-Competition: results, conclusions and implications (2000)The M3-Competition: results, …Out-of-sample tests of forecasting accuracy: an analysis and review (2000)Out-of-sample tests of foreca…Forecasting methods and applications (1993)Forecasting methods and appli…Combining forecasts: A review and annotated bibliography (1990)Combining forecasts: A review…Combining forecasts: A review and annotated bibliography (1989)Combining forecasts: A review…Improved methods of combining forecasts (1984)Improved methods of combining…Time Series Analysis: Forecasting and Control. (1978)Time Series Analysis: Forecas…Experience with Forecasting Univariate Time Series and the Combination of Forecasts (1974)Experience with Forecasting U…Time Series Analysis, Forecasting and Control. (1971)Time Series Analysis, Forecas…The Combination of Forecasts (1969)The Combination of ForecastsUnderstanding machine learning-based forecasting methods: A decomposition framework and research opportunities (2022)Understanding machine learnin…EcoForecast: An interpretable data-driven approach for short-term macroeconomic forecasting using N-BEATS neural network (2022)EcoForecast: An interpretable…Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team (2021)Visitor arrivals forecasts am…Understanding forecast reconciliation (2021)Understanding forecast reconc…The M5 uncertainty competition: Results, findings and conclusions (2021)The M5 uncertainty competitio…Mortality forecasting using stacked regression ensembles (2021)Mortality forecasting using s…FFORMPP: Feature-based forecast model performance prediction (2021)FFORMPP: Feature-based foreca…Classification-based model selection in retail demand forecasting (2021)Classification-based model se…Generalizing the Theta method for automatic forecasting (2020)Generalizing the Theta method…Automatic robust estimation for exponential smoothing: Perspectives from statistics and machine learning (2020)Automatic robust estimation f…Why does forecast combination work so well? (2019)Why does forecast combination…Why do some combinations perform better than others? (2019)Why do some combinations perf…Cross-temporal coherent forecasts for Australian tourism (2019)Cross-temporal coherent forec…Artificial bee colony-based combination approach to forecasting agricultural commodity prices (2019)Artificial bee colony-based c…Expert judgment: Some necessary conditions and an example. (1974)Chapter 4 Forecast Combinations (2006)Forecasting Using Principal Components From a Large Number of Predictors (2002)Macroeconomic Forecasting Using Diffusion Indexes (2002)Forecasting Stock Returns (2013)Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011)A new metric of absolute percentage error for intermittent demand forecasts (2016)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)Time series forecasting using a hybrid ARIMA and neural network model (2003)25 years of time series forecasting (2006)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Forecasting Output and Inflation: The Role of Asset Prices (2003)Forecasting: theory and practice (2022)Principles of forecasting : a handbook for researchers and practitioners (2001)The politics of attention: how government prioritizes problems (2006)Long memory relationships and the aggregation of dynamic models (1980)Understanding spurious regressions in econometrics (1986)Handbook of Economic Forecasting (2013)
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  • 2009

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forecast: Forecasting Functions for Time Series and Linear Models
791 cited

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