get_cost_mape

Get the Mean Absolute Percentage Error (MAPE) to evaluate to forecast accuracy of the cost predictions made by Earned Value Management data.

The MAPE is equal to the average absolute deviation between all EAC(t) forecasts and the final project cost. Cost predictions can be done by eigth forecasting methods and are explained in P2Tracking:get_eac_cost. The PME values are only available when the evm parameter of the P2Simulator:run_simulation has been set to 1 during its execution.

Warning: The MAPE values are average MAPE values for all simulation runs and not for an individual simulation run.

Parameters: 
I/O Type Name Description
output float PFNO Avg_MAPE_EAC
output float PF1 Avg_MAPE_EAC_PF1
output float PFCPI Avg_MAPE_EAC_PFCPI
output float PFSPI Avg_MAPE_EAC_PFSPI
output float PFSPIT Avg_MAPE_EAC_PFSPIT
output float PFSCI Avg_MAPE_EAC_PFSCI
output float PFSCIT Avg_MAPE_EAC_PFSCIT
output float PFweightedSPICPI Avg_MAPE_EAC_PFweightedSPICPI
output float PFweightedSPITCPI Avg_MAPE_EAC_PFweightedSPITCPI
Learn More: 

Step inside PMKC.

Example: 
function ()
        io.write('\n')
end
Class: 
P2Simulator