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An investigation of the impact of using different methods for network meta-analysis
Amalia Emily Karahalios, Georgia Salanti, Simon L Turner, G Peter Herbison, Ian R White, Areti Angeliki Veroniki, Adriani Nikolakopoulou, Joanne E Mckenzie
Sep 08, 2018
BACKGROUND: Network meta-analysis, a method to synthesise evidence from multiple treatments, has increased in popularity in the past decade. Two broad approaches are available to synthesise data across networks, namely, arm- and...
Feature-based intermittent demand forecast combinations
Intermittent demand forecasting is a ubiquitous and challenging problem in production systems and supply chain management. In recent years, there has been a growing focus on developing forecasting approaches for intermittent...
Intermittent demand forecasting Diversity empirical evaluation Forecast combinations time series features /dk/atira/pure/subjectarea/asjc/1400/1408 name=Strategy and Management /dk/atira/pure/subjectarea/asjc/1800/1803 name=Management Science and Operations Research /dk/atira/pure/subjectarea/asjc/2200/2209 name=Industrial and Manufacturing Engineering
Feature-based intermittent demand forecast combinations
Intermittent demand forecasting is a ubiquitous and challenging problem in production systems and supply chain management. In recent years, there has been a growing focus on developing forecasting approaches for intermittent...
Intermittent demand forecasting Diversity empirical evaluation Forecast combinations time series features /dk/atira/pure/subjectarea/asjc/1400/1408 name=Strategy and Management /dk/atira/pure/subjectarea/asjc/1800/1803 name=Management Science and Operations Research /dk/atira/pure/subjectarea/asjc/2200/2209 name=Industrial and Manufacturing Engineering
Forecast with Forecasts
Forecast combinations have been widely applied in the last few decades to improve forecasting. Estimating optimal weights that can outperform simple averages is not always an easy task. In recent years, the idea of using time...
empirical evaluation Forecast combination Forecast diversity Forecasting Prediction intervals /dk/atira/pure/subjectarea/asjc/1700/1700 name=General Computer Science /dk/atira/pure/subjectarea/asjc/2600/2611 name=Modelling and Simulation /dk/atira/pure/subjectarea/asjc/1800/1803 name=Management Science and Operations Research /dk/atira/pure/subjectarea/asjc/1800/1802 name=Information Systems and Management
Forecast with Forecasts
Forecast combinations have been widely applied in the last few decades to improve forecasting. Estimating optimal weights that can outperform simple averages is not always an easy task. In recent years, the idea of using time...
empirical evaluation Forecast combination Forecast diversity Forecasting Prediction intervals /dk/atira/pure/subjectarea/asjc/1700/1700 name=General Computer Science /dk/atira/pure/subjectarea/asjc/2600/2611 name=Modelling and Simulation /dk/atira/pure/subjectarea/asjc/1800/1803 name=Management Science and Operations Research /dk/atira/pure/subjectarea/asjc/1800/1802 name=Information Systems and Management
Forecast Selection and Representativeness
Effective approaches to forecast model selection are crucial to improve forecast accuracy and to facilitate the use of forecasts for decision-making processes. Information criteria or cross-validation are common approaches of...
Forecast Selection and Representativeness
Effective approaches to forecast model selection are crucial to improve forecast accuracy and to facilitate the use of forecasts for decision-making processes. Information criteria or cross-validation are common approaches of...
Power analysis for random-effects meta-analysis
One of the reasons for the popularity of meta-analysis is the notion that these analyses will possess more power to detect effects than individual studies. This is inevitably the case under a fixed-effect model. However, the...