AlFaris, Rand Q. and Khan, Shahjahan (2008) Sine square distribution: a new statistical model based on the sine function. Journal of Applied Probability and Statistics, 3 (1). pp. 163173. ISSN 19306792

Text (Published Version)
AlFaris_Khan.pdf Download (167Kb) 


Text (Published Version  Abstract)
ISOSS2008.pdf Download (74Kb)  Preview 
Abstract
This paper introduces a new continuous distribution based on the sine function. The proposed Sine Square distribution has one parameter and its domain depends on this parameter. The probability density function f(x) of a Sine Square variable X as well as its cumulative distribution function F(x) are defined. The formulas for the rth raw moment and central
moments, moments generating function (m.g.f.), characteristic function (c.f.) and some other properties of the new distribution are provided. A method to generate random variables from the Sine Square distribution is analyzed and applied.
Statistics for this ePrint Item 
Item Type:  Article (Commonwealth Reporting Category C) 

Refereed:  Yes 
Item Status:  Live Archive 
Additional Information (displayed to public):  © 2011 ISOSS Publications. Selected Papers from the 9th Islamic Countries Conference on Statistical Sciences (ICCSIX). Deposited with blanket permission of publisher. 
Depositing User:  Professor Shahjahan Khan 
Faculty / Department / School:  Historic  Faculty of Sciences  Department of Maths and Computing 
Date Deposited:  08 Oct 2008 23:37 
Last Modified:  29 Oct 2014 23:31 
Uncontrolled Keywords:  sine function; probability and distribution functions; generating functions; simulation of random variables 
Fields of Research (FoR):  01 Mathematical Sciences > 0104 Statistics > 010404 Probability Theory 01 Mathematical Sciences > 0104 Statistics > 010405 Statistical Theory 
SocioEconomic Objective (SEO):  E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences 
URI:  http://eprints.usq.edu.au/id/eprint/4511 
Actions (login required)
Archive Repository Staff Only 