Author: Yau, Ka Ho
Title: Inverted probability loss functions and its applications
Advisors: Leung, Bartholomew P. K. (AMA)
Degree: M.Phil.
Year: 2015
Subject: Management science -- Mathematical models.
Industrial management -- Mathematical models.
Decision-making -- Mathematical models
Hong Kong Polytechnic University -- Dissertations
Department: Department of Applied Mathematics
Pages: xiii, 139 leaves : illustrations ; 30 cm
Language: English
Abstract: In most statistical and decision problems, nearly no attention is paid to the precise mathematical form of the loss function. However, the choice of a particular loss function seriously affects the resulting inferences and estimations. This dissertation investigates a general class of loss functions based on the reflection or inversion of a probability density function, Inverted Probability loss function, which was proposed by Spiring and Yeung (1998). We modified the Inverted Probability loss function to be a more generalisation of the original one. To the best of my knowledge and belief, it is the first time to establish such results in the literature. We firmly advocate that there are some novelties in the Inverted Probability Loss Functions and there are even more applications when applying them. In this report, we show the broad coverage and the flexibility of the Loss Functions to make a more robust expected loss.
Rights: All rights reserved
Access: open access

Files in This Item:
File Description SizeFormat 
b2806835x.pdfFor All Users2.18 MBAdobe PDFView/Open


Copyright Undertaking

As a bona fide Library user, I declare that:

  1. I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
  2. I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
  3. I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.

By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.

Show full item record

Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/7920