Date of Award
9-1-2018
Thesis Type
masters
Document Type
Thesis (Restricted Access)
Divisions
science
Department
Faculty of Science
Institution
University of Malaya
Abstract
This research proposes a parameter estimation method that minimizes a probability generating function (pgf) based power divergence with a tuning parameter to mitigate the impact of data contamination. Special cases arise when the tuning parameter approaches zero, resulting in a Kullback-Leibler type divergence, and when it takes on the value of one, resulting in a pgf-based
Note
Dissertation (M.A.) – Faculty of Science, University of Malaya, 2018.
Recommended Citation
Tay, Siew Ying, "Parameter estimation using generating function based minimum power divergence measure / Tay Siew Ying" (2018). Student Works (2010-2019). 5831.
https://knova.um.edu.my/student_works_2010s/5831