M.Phil / MS

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This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.

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End date: 2025Subject: search.filters.subject.sp16

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    Generalized Ratio Type Exponential Estimators for the Population Mean Using Ranked Set Sampling
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2018) Amjad Ali; SP16-RST-002; LHR TP 4837; Dr. Muhammad Ismail
    The dominance of using ranked set sampling, for estimating the mean of a population, as compare to simple random sampling is well reputable. This technique is useful when visual ordering of a small set of size “m” can be made simply and precisely, since exact measurement of a value is most of the times very hard to obtain. In this dissertation, exponential ratio type estimators are proposed for evaluating the population mean by using ranked set sampling. We found through numerical results that the results of proposed ratio type estimators which is estimated under ranked set sampling is more reliable and competent than the simple random sampling (SRS) and some other already existed estimators under SRS are suggested by Cochran (1977), Parsad 1989, Bahl and Tuteja (1991). The comparison is also made with estimators under ranked set sampling by Samawi and Muttalak (1996), Rabail (2014) and Gajendra , Zeeshan and Carlos (2017).
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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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    Estimation of Population Mean by Using Robust Regression
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2018) Salah ud din Asghar; SP16-RST-003; LHR TP 5250; Dr. Muhammad Noor-ul-amin
    In the linear regression problems, ordinary least square (OLS) estimates violate in the presence of outliers as according to the assumptions of the OLS model that there should not be outliers in the data. More specifically, since the classical procedures are not applicable to the case of outliers presence. So, for the purpose of estimation there is another approach which handles this situation of outliers that is robust regression. Robust regression is an important tool for investigating data that are tainted with outliers and provide efficient results. In robust regression, estimates completely reject the effect of outliers and provide good estimates of the population parameter. In this work we focus on the problem of outliers occur in the data which provides a bad estimate of the population mean. In this dissertation, redescending M-estimator and ratio estimator have been proposed to estimate finite population mean using the information from auxiliary variable. Discussions have been made about the robust estimation method based on M-estimation, outliers, ratio estimators and auxiliary variable in Chapter 1. The literature about the robust regression and ratio estimator is discussed in Chapter 2. This research work is based on the two main chapters. The 3rd and 4th Chapters are the most important chapters of the thesis. For the first strategy, in the 3rd Chapter a redescending M-estimator is proposed by reworking on the redescending M-estimator proposed by Insha-ullah et al. (2006) which assign a weight closer to zero to the extreme values and closer to one to the good observations. Most of the redescending M-estimators are solved by iteratively reweighted least square method. For the second strategy we adopt the ratio estimators proposed by Kadilar and Cingi (2004) in the 4th Chapter and replace OLS coefficient with our redescending M-estimator proposed in 3rd Chapter in these ratio estimators. In both parts numerical illustrations and simulation studies were used to analyze the results of the proposed estimators with the comparative estimators to achieve the main results of the research. The intention of this research is to analyze, introduce and improve robust estimation methodologies to solve real life problems such as outliers in data. And finally in 5th chapter conclusion is written based upon whole the results of research.
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    Some New Insights of Exponential Weighted Moving Average Control Chart with Fuzzy Control Lenses
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2018) Muhammad Javed; SP16-RST-001; LHR TP 5249; Dr. Tajammal Hussain
    Statistical process control (SPC) is an approaching path that analyzes processes despite the fact whether they are under statistical control or out of control. So, Control charts are commonly employed for this purpose. Possibly, sample data may possess some uncertainties occurring owing to systems of measurement and conditions of the surrounding environment, for this purpose fuzzy numbers or language variables are usable to seize such form of uncertainties. Thereby, the well-known control charts, exponentially weighted moving average control chart (EWMA) to univariate data are formed up under the environment that is fuzzy one. The fuzzy EWMA control charts (FEWMA) are also usable in order to detect minute changes in the data presented by fuzzy numbers. FEWMA lessens various mistaken and unreliable decisions by catering further flexibleness upon the control limits. As far as the production process is monitored and controlled by dint of FEWMA control chart.
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    Estimation of Mean for a Finite Population Using Sub Sampling of Non-Responden
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2018) Iqra Ehsan; SP16-RST-004; LHR TP 4834; Dr. Aamir Sanaullah
    In Chapter 1, introduction about Survey sampling, use of auxiliary information in context of single and two-phase sampling has been deliberated. Further in Chapter 1, the problem of non-response in two has been deliberated. Different methods dealing non-response have been deliberated by different authors but Hansen-Hurwitz sub-sampling has been deliberated in more detail. In Chapter 2, the literature regarding the use of classical sampling design has been deliberated. The literature about some existing estimators for single and two-phase sampling has been deliberated. Various work of non-response has also been specified in Chapter 2. Research methodology of proposed work has been given in chapter # 3. The major contribution of this study starts from Chapter 4 & 5. In chapter 4, we proposed some estimators using single auxiliary variables when population mean of auxiliary variable is available under simple random sampling in the occurrence of non- response. Further the properties of the proposed class of estimators have been deliberated in chapter 4. Also optimum conditions for which proposed class of estimators has minimum MSE’s has been deliberated with their empirical studies. In chapter 5, we proposed some estimators using single auxiliary variable when population mean of auxiliary variable is not available in prior under simple random sampling in the occurrence of non- response. Further the properties of the proposed class of estimators have been deliberated in chapter 5. Also optimal conditions for which proposed class of estimators attain minimum MSE’s has been deliberated with their empirical studies. In Chapter 6 conclusion has been drawn about the generalized class of estimators proposed in this study. Finally it is shown that the proposed estimators are more efficient as compare to the existing estimators of literature
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