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This paper sets forth a synergy of existing statistical theories to obtain a clearcut model for calculating forecasts with prediction intervals, named the “WK1 model”.
Many predictive models calculate a linear or nonlinear trend from the historical data and generate a single, discrete forecast value, being a single dot on this defined trend line (i.e. point forecast).
Our “WK1 model” increases the power of such a single discrete point forecast by adding its probable accuracy with top and bottom limits. The decisionmaker obtains thus different ranges of values, each within several predefined prediction intervals to assess for that specific outcome probability.
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