Web Based Application Maintenance Cost Estimation Modeling Using Bayesian SEM

Abstract:

The objectives of this research were to find out the Structural equation modeling coefficient and other parameter estimation under unknown prior distribution and compare this new model’s coefficient accuracy with the former model on “Web based application maintenance cost estimation multi group modeling” [16]. This new coefficient and parameter were estimated with Bayesian analysis instead of Maximum likelihood estimation (ML). The input model used in Bayesian analysis was started from the ML-model result [16]. The new values were replaced into the former model then MMRE was detected from 30 (testing) completed software maintenance projects while 192 projects were used for SEM model training. The result of cross validation was about 44.08% for Bayesian analysis refined SEM model while the ML-SEM model was 47.58%.

• Periodical: Advanced Materials Research (Volumes 403-408)
• Pages: 3704-3708
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.403-408.3704
• Online since: November 2011
• Authors: Somchai Prakancharoen
• Keywords: Bayesian Analysis, Factor Analysis (FA), Structural Equation Modeling (SEM), Web Based Application Software Maintenance

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DOI: 10.30892/gtg.29216-491

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