Evaluation of Calibration Techniques to Build Software Cost Estimation Models
Keywords:
Ordinary Least Squares Regression, Bayesian Analysis, Multiple Regression Technique, Develop for Reusability(RUSE), Constrained Multiple Regression Technique, Constrained Minimum Sum of Square Errors(CMSE), Constrained Minimum Sum of Absolute Errors, Required Development Schedule(SCED)Abstract
This research paper describes three calibration techniques, namely ordinary least squares regression, Bayesian analysis, and constrained regression technique, which are applied to calibrating the cost drivers of the model.
Ordinary least squares (OLS) regression is the most popular technique used to build software cost estimation models. In COCOMO, the OLS is used for many purposes, such as analyzing the correlation between cost drivers and the effort and generating coefficients and their variances during the Bayesian analysis.
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