Department of Statistics

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Author: search.filters.author.Dr. Riffat JabeenSubject: search.filters.subject.Statistics, computer and systems science

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    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 7203
    Pareto 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.
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    Development of Estimators for Population Mean of Sensitive Variable in Survey Sampling
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2017) Muhammad Kamran ASLAM; SP16-RST-005; LHR TP 4833; Dr. Riffat Jabeen
    In Chapter 1, introduction about Survey sampling, use of auxiliary in formation in context stratified random sampling has been deliberated. Further in Chapter 1, Different methods dealing randomized response have been deliberated by different authors but Hansen-Hurwitz sub sampling has been consider in more detail. In Chapter 2, the literature regarding the use of classical sampling de sign has been deliberated. The literature about some existing estimators for calibration estimator under stratified random sampling has been ex press. Various work of randomized response has also been specified in Chapter 2. Some well-known existing randomized response model, scrambling vari able under auxiliary and study variable, with randomized response or complete response have been reproduced in Chapter3. The major con tribution of this study starts from next Chapter. In Chapter 4, new estimators using auxiliary information have been proposed for calibration estimator in randomized response under strat ified random sampling scheme. The mean square error each estimator has been derived along. In Chapter 5 conclusion has been drawn about the generalized class of estimators proposed in this study. Finally it is shown that the propose estimator II is more efficient than proposed estimator I.
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    Development Of Calibration Log Estimator to Estimate Population Mean Using Randomized Response Technique
    (Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Rehmina; CIIT/FA19-BST-011/LHR; Dr. Riffat Jabeen; LHR TP 9944
    Calibration method is a useful method in daily life meanwhile it allows us to gather a single sample without repeating the process. In the presence of sensitive information, we calculate the variation of population with the help of calibration method. We proposed calibration log ratio estimator by using the method of (Jabeen, et al. 2022) in the presence of sensitive data.
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    Construction of Calibration Log Ratio Estimator to Estimate Population Variance
    (Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Khafiza Afzal; CIIT/FA19-BST-003/LHR; Dr. Riffat Jabeen; LHR TP 9938
    Calibration is frequently used to improve the population parameter estimation’s accuracy using auxiliary data. In our study, we have introduced the calibration and the calibration log variance estimator for estimating the population variance. The study proposes the calibration variance log estimators using chi square distance measure and different calibration constraints respectively. Our findings indicate that the suggested calibration variance estimator performed better than the existing estimator.