說明 
96 p 
附註 
Source: Dissertation Abstracts International, Volume: 7102, Section: B, page: 1088 

Adviser: Alan D. Hutson 

Thesis (Ph.D.)State University of New York at Buffalo, 2010 

A common assumption for a number of statistical applications involving continuous data, is to assume the data are normally distributed. In the event the normality assumption is in question BoxCox transformations to the data or the use of nonparametric and semiparametric models are often utilized. An alternative approach is to consider utilizing the epsilonskewnormal (ESN) distribution developed by Mudholkar and Hutson (2000). We create extensions based on the ESN model and apply and extend Tobit models and binormal receiver operating characteristic (ROC) curves. We examine the behavior of the maximum likelihood estimates for model parameters via simulation study and show that they are well behaved. We also introduce a new family of distributions called the logepsilonskewnormal (LESN) distribution and derive its properties. We illustrate its utility in the context of accelerated life failure modeling. We will also lay out a plan for our future work 

School code: 0656 
Host Item 
Dissertation Abstracts International 7102B

主題 
Statistics


0463

Alt Author 
State University of New York at Buffalo. Biostatistics

