Model Prediction using Correlation In Contrast With QQ-Plot
Kotte Sandeep1, R. Satya Prasad2

1Kotte Sandeep, Assistant Professor, Department of CSE, Dhanekula Institute of Engineering & Technology, Vijayawada, A.P, India.
2R. Satya Prasad, Professor & Head, Department of CSE, Acharya Nagarjuna University, Guntur, A.P, India.

Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 2407-2410 | Volume-8 Issue-9, July 2019 | Retrieval Number I7782078919/19©BEIESP | DOI: 10.35940/ijitee.I7782.078919
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Abstract: In this paper, we mainly focused on developing reliable, efficient and error free software products by following practices. The software which follows proper testing techniques has less failure rate. To analyze the information or data, it should be understood first that is better to be done with the best suited model. Selection of the best suited model isn’t a simple task, and there are different methods in it. One such method is qq-plot, however, it’s not a quantified measure and time overwhelming process. We proposed a qq-plot and quantified measure “correlation factor” to demonstrate its use to choose the best fit model for information among different models being referred to.
keyword: Correlation factor, QQ-Plot, Best fit, LPETM, MLE, HPP, NHPP

Scope of the Article: Probabilistic Models and Methods