Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
Articles by Jayanthi Arasan
Total Records ( 2 ) for Jayanthi Arasan
  Al Omari Mohammed Ahmed , Noor Akma Ibrahim , Mohd Bakri Adam and Jayanthi Arasan
  We consider the Weibull distribution which has been extensively used in life testing and reliability studies of the strength of materials. The maximum likelihood method is the usual frequentist approach in the parameter estimate for parametric survival data. In this study, we divert from this platform and use the Bayesian paradigm instead. The Jeffreys and extension of Jeffreys prior with the squared loss function are considered in the estimation. The Bayes estimates of the survival function and hazard rate of the Weibull distribution with censored data obtained using Lindley’s approximation are then compared to its maximum likelihood counterparts. The comparison criteria is the Mean Square Error (MSE) and the performance of these three estimates are assessed using simulations considering various sample sizes, several specific values of Weibull parameters and several values of extension of Jeffreys prior. The maximum likelihood estimates of survival function and hazard rate are more efficient than their Bayesian counterparts, however, the extension of Jeffreys is better than the maximum likelihood for certain conditions.
  Habshah Midi , Ehab A. Mahmood , Abdul Ghapor Hussin and Jayanthi Arasan
  Mean direction is a good measure to estimate circular location parameter in univariate circular data. However, it is bias and cause misleading when the circular data has some outliers, especially with increasing ratio of outliers. Trimmed mean is one of robust method to estimate location parameter. Therefore in this study, it is focused to find a robust formula for trimming the circular data. This proposed method is compared with mean direction, median direction and M estimator for clean and contaminated data. Results of simulation study and real data prove that trimmed mean direction is very successful and the best among them.
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility