VoseTimeSMEUniform

VoseTimeSMEUniform({MinValues}, {MaxValues}, CorrelationFactor)

Time series function modeling a variable estimated for each period by minimum and maximum values

• {MinValues} is an array of the minimum possible values for each period of the forecast.

• {MaxValues} is an array of the maximum possible values for each period of the forecast.

• CorrelationFactor applies a positive correlation between generated values within each period of the series. CorrelationFactor must lie on [0,1]. Optional, set to zero if omitted.

Explanation and Uses

The SMEUniform time series function provides an easy, subjective way to specify a time series with some key features:

Growth and spread over time can be controlled by changing the {MinValues} and {MaxValues} array values.

Correlation between periods can be specified with a single parameter. The level of correlation is best selected by reviewing the example pathways that are generated in the interface each time one clicks the Generate button. Look at the range of variation from one period to the next across the entire series and adjust the CorrelationFactor until it looks reasonable. If you believe that there is correlation across the series you will likely settle on a value above 0.4 since lower levels of correlation are not immediately obvious to the eye. You will want to use correlation, for example, when the variable being forecast will tend to be high in each year if it is high in the first year: for example, a forecast of sales of a new product, when it either takes off because it is appealing to potential clients, or doesn’t; or the use of a new vaccine where people are generally convinced of its value, or not.