2018International Journal of Mathematics in Operational ResearchRequires access

Generate random variates using a newly introduced approximation to cumulative density of lower truncated normal distribution for simulation applications

Mohammad M. Hamasha

Open publisher page 0 citations

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.

About this research paper

What this paper is about

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.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available 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.

Key concepts: Cumulative distribution function, Truncated normal distribution, Mathematics, Inverse, Normal distribution, Half-normal distribution, Applied mathematics, Simple (philosophy)

Related papers

Back to paper searchBrowse research topicsOriginal source
Generate random variates using a newly introduced approximation to cumulative density of lower truncated normal distribution for simulation applications — Research Paper | ScholarLens