Mean Absolute Deviation for Linear Loss scenarios.
Syntax
meanabs_dev(matrix) |
short call |
meanabs_dev_name(matrix) |
call with optional name |
Parameters
matrix is a Matrix of Scenarios:
where the header row contains names of variables (except scenario_probability, and scenario_benchmark). Other rows contain numerical data. The scenario_probability, and scenario_benchmark columns are optional.
Mathematical Definition
Mean Absolute Deviation function is calculated as follows
,
where:
is Mean Absolute Penalty function
,
is Loss Function (See section Loss and Gain Functions)
is an argument of Mean Absolute Deviation function.
Example
Case Studies with Mean Absolute Deviation
See also
Mean Absolute Error, Mean Absolute Error Normal Independent, Mean Absolute Error Normal Dependent, Mean Absolute Risk, Mean Absolute Risk for Gain, Mean Absolute Risk Normal Independent, Mean Absolute Risk for Gain Normal Independent, Mean Absolute Risk Normal Dependent, Mean Absolute Risk for Gain Normal Dependent, Mean Absolute Deviation Normal Independent, Mean Absolute Deviation Normal Dependent