Maximum likelihood and Bayes estimators of the parameters, survival function (SF) and hazard rate function (HRF) are obtained for the three-parameter exponentiated Burr type XII distribution when sample is available f...Maximum likelihood and Bayes estimators of the parameters, survival function (SF) and hazard rate function (HRF) are obtained for the three-parameter exponentiated Burr type XII distribution when sample is available from type II censored scheme. Bayes estimators have been developed using the standard Bayes and MCMC methods under square error and LINEX loss functions, using informative type of priors for the parameters. Simulation comparison of various estimation methods is made when n = 20, 40, 60 and censored data. The Bayes estimates are found to be, generally, better than the maximum likelihood estimates against the proposed prior, in the sense of having smaller mean square errors. This is found to be true whether the data are complete or censored. Estimates improve by increasing sample size. Analysis is also carried out for real life data.展开更多
The </span></span><span><span><span style="font-family:"">software reliability model is the stochastic model to measure the software <span>reliability quantitatively....The </span></span><span><span><span style="font-family:"">software reliability model is the stochastic model to measure the software <span>reliability quantitatively. A Hazard-Rate Model is </span></span></span></span><span><span><span style="font-family:"">the </span></span></span><span><span><span style="font-family:"">well</span></span></span><span><span><span style="font-family:"">-</span></span></span><span><span><span style="font-family:"">known one as the</span></span></span><span><span><span style="font-family:""> typical software reliability model. We propose Hazard-Rate Models Consider<span>ing Fault Severity Levels (CFSL) for Open Source Software (OSS). The purpose of </span><span>this research is to </span></span></span></span><span><span><span style="font-family:"">make </span></span></span><span><span><span style="font-family:"">the Hazard-Rate Model considering CFSL adapt to</span></span></span><span><span><span style="font-family:""> </span></span></span><span><span><span style="font-family:"">baseline hazard function and 2 kinds of faults data in Bug Tracking System <span>(BTS)</span></span></span></span><span><span><span style="font-family:"">,</span></span></span><span><span><span style="font-family:""> <i>i.e.</i>, we use the covariate vectors in Cox proportional Hazard-Rate</span></span></span><span><span><span style="font-family:""> Model. Also, <span>we show the numerical examples by evaluating the performance of our pro</span><span>posed model. As the result, we compare the performance of our model with the</span> Hazard-Rate Model CFSL.展开更多
基金supported by the Provincial Natural Science Research Project of Anhui Colleges(KJ2013A137)the Natural Science Foundation of Anhui Province(1408085MA07)the PhD Research Startup Foundation of Anhui Normal University(2014bsqdjj34) which facilitated the research visit of the first author to McMaster University,Canada
基金supported by the National Natural Science Foundation of China(Grant No.11201003)the Provincial Natural Science Research Project of Anhui Colleges(Grant No.KJ2016A263)+1 种基金the Natural Science Foundation of Anhui Province(Grant No.1408085MA07)the PhD Research Startup Foundation of Anhui Normal University(Grant No.2014bsqdjj34)
文摘Maximum likelihood and Bayes estimators of the parameters, survival function (SF) and hazard rate function (HRF) are obtained for the three-parameter exponentiated Burr type XII distribution when sample is available from type II censored scheme. Bayes estimators have been developed using the standard Bayes and MCMC methods under square error and LINEX loss functions, using informative type of priors for the parameters. Simulation comparison of various estimation methods is made when n = 20, 40, 60 and censored data. The Bayes estimates are found to be, generally, better than the maximum likelihood estimates against the proposed prior, in the sense of having smaller mean square errors. This is found to be true whether the data are complete or censored. Estimates improve by increasing sample size. Analysis is also carried out for real life data.
文摘The </span></span><span><span><span style="font-family:"">software reliability model is the stochastic model to measure the software <span>reliability quantitatively. A Hazard-Rate Model is </span></span></span></span><span><span><span style="font-family:"">the </span></span></span><span><span><span style="font-family:"">well</span></span></span><span><span><span style="font-family:"">-</span></span></span><span><span><span style="font-family:"">known one as the</span></span></span><span><span><span style="font-family:""> typical software reliability model. We propose Hazard-Rate Models Consider<span>ing Fault Severity Levels (CFSL) for Open Source Software (OSS). The purpose of </span><span>this research is to </span></span></span></span><span><span><span style="font-family:"">make </span></span></span><span><span><span style="font-family:"">the Hazard-Rate Model considering CFSL adapt to</span></span></span><span><span><span style="font-family:""> </span></span></span><span><span><span style="font-family:"">baseline hazard function and 2 kinds of faults data in Bug Tracking System <span>(BTS)</span></span></span></span><span><span><span style="font-family:"">,</span></span></span><span><span><span style="font-family:""> <i>i.e.</i>, we use the covariate vectors in Cox proportional Hazard-Rate</span></span></span><span><span><span style="font-family:""> Model. Also, <span>we show the numerical examples by evaluating the performance of our pro</span><span>posed model. As the result, we compare the performance of our model with the</span> Hazard-Rate Model CFSL.
