Creation of an MLR Profile
In this process you specify the parameters that the system uses for causal analysis with multiple linear regression (MLR). These are:
You have created a master forecast profile.
If you use key figures, you can define a time shift between cause and effect. For example the demand for a consumer product may depend on the income tax rate. However since most employee are paid at the end of the month, it takes at least one month till the effect of a reduction in the tax rate will be seen.
If you want the system to generate alerts when measures of fit are not reached or exceeded, enter a diagnosis group. See alsoMeasures of Fit.
Measured Value Error
In certain circumstances it is useful to be able to determine how the system determines the error in a measured value. The system can assume a normal or a Poison distribution. In the case of a normal distribution, you can specify whether the error variance is constant or variable. If it is constant, you can enter a value in the Sigma field. If it is variable, the system calculates the necessary values.
In general you do not need to make an entry in this field. For more details, refer to the F1 help.