M.Phil / MS
Permanent URI for this collectionhttps://repository.cuilahore.edu.pk/handle/123456789/63
This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.
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Item Control Charts for new Reflected Pareto Distribution(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) Huma Khalid; FA19-RST-007; Dr. Riffat Jabeen; LHR TP 7203Pareto distribution has vast application in different fields of medical and engineering sciences. In this thesis, we have proposed a new Reflected Pareto Distribution (RPD) using Cohen (1973) to reflect the parameter of distribution. We derive different mathematical properties such as mean, variance, rth moment. Reliability measures are also discussed including Survival Function, Hazard function and reversed hazard function. The method of Maximum Likelihood Estimator and Modified maximum likelihood estimator is used to estimate the model parameters. We used three different data sets to show the performance of Reflected Pareto distribution over already existing probability distributions. We also construct the control charts to monitor the shape parameter for reliability processes using Shewhart control chart and Exponentially weighted moving averages control chart. We compare the performance of maximum likelihood estimator and modified maximum likelihood estimator for the shape parameter of Reflected Pareto distribution.Item Some Memory Type Estimators for Population Variance in Survey Sampling(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Umme Habiba; CIIT/FA23/RST/004/LHR; Dr. Riffat Jabeen; LHR TP 9874Reducing and estimating population variation is important in survey sampling. These variations can occur in any sampling design, including stratified random sampling. In stratified random sampling the difference in stratum weights increase the variation. This problem can be control with the use of calibration techniques, and auxiliary information. By using this technique, we can increase the accuracy and efficiency of estimator. Improving the efficiency of estimator for population variance estimation is the primary goal of this study. Both exponentially weighted moving average (EWMA) and extended exponentially weighted moving average (EEWMA) memory type statistics are used in this study to estimate population variance. EWMA use only current data whereas EEWMA use both current and past observations. The EWMA and EEWMA statistics are used to build the calibration variance and ratio estimators. The mean square errors are calculated, and the effectiveness of the estimators is illustrated through a discussion of mathematical comparisons. To assess the efficiency of the proposed memory type estimators, a simulation study is conducted and MSE are compare with existing estimators. The results show that proposed estimators are perform efficiently as compared to the existing estimators