The accuracy of combining judgemental and statistical forecasts

Article Abstract:

Commonly employed in applications by themselves, or in connection with computer compiled forecasts, judgement-based forecasting techniques have not been adequately tested for accuracy, especially in areas where statistical and judgemental forecasts are combined. In an investigation of combined forecasts, especially through simple averaging, both general accuracy and the impact on accuracy by time series characteristics are evaluated. The experiment is described, and the two judgemental techniques and experiment's subject groups are discussed. The analysis methodology, its use of mean absolute percentage error, and stratification of the sample, are reviewed. Results indicate that combining forecasts exhibit greater accuracy than single forecasts, and simple averaging is the best method for combining judgemental forecasts.

Research, Technology application, Economic forecasting, Business forecasting

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Interaction of judgemental and statistical forecasting methods: issues & analysis

Article Abstract:

A review of research on the use of judgment in statistical forecasting indicates that there is validity in the use of judgment in forecasting. The use of judgment is valid if the judgmental process is made explicit by using a type of decomposition or audit trail. The judgmental factors in forecasting include the selection of variables and the analysis of data. The types of research that have helped to substantiate the more critical view of the use of judgment in forecasting include bootstrapping research and quality-of-judgment research. Judgmental forecasters should establish the nature of the comparison, the experiment, and the methods.

Methods, Analysis, Usage, Management research, Judgment, Judgment (Psychology), Business literature

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Constructing a Complex Judgemental Model: An Index of Trauma Severity

Article Abstract:

A multiattribute model was developed to represent one surgeon's professional judgement of the severity of different physical injuries suffered by patients. It was developed to indicate the usefullness of multiattribute utility models to quantify professional judgement. It illustrates a complicated multiattribute assessment incoporating complex interrelationships between variables. A trauma severity index was developed. A diagram shows the hierarchy of trauma severity concerns.

Management science, Medicine, Mathematical models, Medical research, Modeling, Data modeling software, Models, Medical Diagnosis, Decision Making, Operations Research, Treatment Planning

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