Generate random variates using a newly introduced approximation to cumulative density of lower truncated normal distribution for simulation applications
by Mohammad M. Hamasha
International Journal of Mathematics in Operational Research (IJMOR), Vol. 13, No. 3, 2018

Abstract: In this paper, the lower side truncated cumulative normal distribution is approximated by a simple function, the inverse of the function is derived, and random variates are explained how to be generated from the introduced inverse approximation. The introduced approximation is derived from Aludaat and Alodat's model of approximating cumulative normal distribution. The accuracy of the introduced function is investigated in term of maximum absolute error (i.e., 0.003944). This level of accuracy is possibly the best comparing all previous similar models to the best of the author's knowledge.

Online publication date: Tue, 25-Sep-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mathematics in Operational Research (IJMOR):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com