• Login
    View Item 
    •   Repository Home
    • Master Theses and Dissertations(MST)
    • MST-School of Pure and Applied Sciences
    • MST-Department of Statistics and Actuarial Science
    • MST-Department of Statistics and Actuarial Science
    • View Item
    •   Repository Home
    • Master Theses and Dissertations(MST)
    • MST-School of Pure and Applied Sciences
    • MST-Department of Statistics and Actuarial Science
    • MST-Department of Statistics and Actuarial Science
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Robust M-Estimators of the Population Mean.

    Thumbnail
    View/Open
    Full text Thesis (2.195Mb)
    Date
    2018-07
    Author
    Mutuguta, Bernard Githui
    Metadata
    Show full item record
    Abstract
    Valuable information may be contained in outliers. Data collected from many medical equipment such as the ECG time-series may result in unusual patterns, a situation that may represent disease conditions. Some outliers may therefore provide an insight into crucial information that may lead to the discovery of new knowledge.Due to the di culties involved in the study of outliers, majority of current research works have chosen not to out-rightly reject the outliers but have adopted methods that accommodates them but have their in uence reduced to some degree. This has resulted in the development of estimation and testing techniques that have yielded robust estimation. Three robust M-estimators (the Huber, the Hampel and the Tukey's biweight) were adopted in this paper with an aim of comparing their e ciency in the estimation of population mean in an asymmetrical distribution. Simulation was used to generate a normal population which was then contaminated with a few outlying observations. A simple example illustrated how the comparison of the M- estimators was carried out on real data. On the basis of the ndings from this research, the M-estimator that turned out to be the best, was the Tukey's biweight followed by the Hampel's and the Huber's was the weakest of the three. However all the three M-estimators yielded unbiased estimates of the population mean.
    URI
    http://ir-library.ku.ac.ke/handle/123456789/19223
    Collections
    • MST-Department of Statistics and Actuarial Science [7]

    Designed by Library ICT Team copyright © 2017 
    Contact Us | Send Feedback

     

     

    Browse

    All of RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Designed by Library ICT Team copyright © 2017 
    Contact Us | Send Feedback