@article {28156,
	title = {When should we (not) use the mean magnitude of relative error (MMRE) as an error measure in software development effort estimation?},
	journal = {Information and Software Technology},
	volume = {143},
	year = {2022},
	month = {03/2022},
	pages = {106784},
	publisher = {Elsevier},
	abstract = {Context: The mean magnitude of relative error (MMRE) is an error measure frequently used to evaluate and compare the estimation performance of prediction models and software professionals.Objective: This paper examines conditions for proper use of MMRE in effort estimation contexts.Method: We apply research on scoring functions to identify the type of estimates that minimizes the expected value of the MMRE.Results: We show that the MMRE is a proper error measure for estimates of the most likely (mode) effort, but not for estimates of the median or mean effort, provided that the effort usage is approximately log-normally distributed, which we argue is a reasonable assumption in many software development contexts. The relevance of the findings is demonstrated on real-world software development data.Conclusion: MMRE is not a proper measure of the accuracy of estimates of the median or mean effort, but may be used for the accuracy evaluation of estimates of most likely effort.},
	author = {J{\o}rgensen, Magne and Halkjelsvik, Torleif and Liest{\o}l, Knut}
}
