Point and Interval Estimates of Weibull Distribution to Progressively Type II Censored Data by order statistics Approach
Sujatha.V1, Ravanan. R2, Ramakrishnan. M3
1Sujatha.V Research, Scholar MTW University, Department of Mathematics, VIT University, Vellore. (Tamil Nadu) India.
2Ravanan .R Professor, Department of Statistics, Presidency College, Chennai, (Tamil Nadu) India.
3Ramakrishnan.M. Assistant Professor, Department of Mathematics, RKM Vivekananda college, Chennai, (Tamil Nadu) India.
Manuscript received on 25 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 370-374 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2239037619/19©BEIESP
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Abstract: In recent years, progressive censoring had a tremendous development in life testing models. If the samples do not experience the failure until the failure time period or up to the study period, then the inference on type I censoring models leads to poor statistical analysis. Instead of fixing the time failure, if number of failure components is fixed then type II censoring leads to some information results, associated with the model parameters. In both the censoring schemes none of the sample units are removed during the experiment period. But in progressive censoring scheme the number of observations and removals of the samples are fixed. In this study, point and interval estimates of the Weibull distribution for progressively type II censored data were estimated by maximum likelihood parameters, and also an exact confidence interval and region are constructed. A numerical example is presented over here to illustrate the proposed method
Keywords: Confidence-interval, Progressive type II censored samples, Point and interval estimates, Type II Censoring
Scope of the Article: Artificial Intelligence Approaches to Software Engineering