A proposed approach for approximating lower truncated normal cumulative distribution based on Hamaker's Model
by Mohammad M. Hamasha; Faisal Aqlan; Abdulaziz Ahmed
International Journal of Reliability and Safety (IJRS), Vol. 15, No. 3, 2021

Abstract: In various workplaces, reliability engineers face many cases where the normal distribution is truncated from the lower side. For example, the distribution of used devices is a truncated distribution. Moreover, the distribution of products after screening and removing the unfit products is truncated distribution. Although there are many mathematical models and algorithms to approximate normal cumulative distribution, there is a limited number of approximations for truncated normal distributions. This paper proposes a new accurate approximation for the lower truncated normal distribution. The proposed model is simple and easy to implement. Numerical experiments show that the model accuracy, represented by the maximum absolute deviation from the true values, is about 0.00124 for the entire definition domain [Z_L : ∞], where Z_L is the point at truncation, and it takes values up to zero (i.e., Z_L ∈ [-∞ : 0]). The proposed model can be used for quick manual calculations, especially if the intention is to avoid purchasing an expensive specialised program/software.

Online publication date: Tue, 07-Jun-2022

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 Reliability and Safety (IJRS):
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