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    Isotonic regression through the Merge and Chop Algorithm for application in statistical inference

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    Thesis (311.9Kb)
    Date
    2016-05
    Author
    Skala, Jacob Thomas
    Advisor
    Hu, Xiaomi
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    Abstract
    In this paper, the theory for the application of the Merge and Chop Algorithm are defined and proven. The algorithm is used to find isotonic regressions in more situations than comparable methods. A program is included with this paper for computing the desired isotonic regressions through the algorithm. These isotonic regressions can then be used to perform more accurate and powerful hypothesis tests. This paper also defines these possible areas of utilization with use of restricted maximum likelihood estimators and likelihood ratio tests.
    Description
    Thesis (M.S.)--Wichita State University, Fairmount College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and Physics
    URI
    http://hdl.handle.net/10057/12676
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