Neutrosophic Inverse Gaussian Distribution in Economic Policy  Design under Indeterminacy

Ahmedia Musa M. Ibrahim; Zahid Khan

Authors

Ahmedia Musa M. Ibrahim Finance Department, College of Business Administration in Hawtat Bin Tamim, Prince Sattam bin Abdulaziz University, Hawtat Bin Tamim, Saudi Arabia
Zahid Khan Department of Quantitative Methods, Pannon Egyetem, Veszprem, H-8200, Hungary.

Keywords:

Neutrosophic probability, inverse Gaussian distribution, economic policy, indeterminacy, uncertainty modeling, financial risk.

Abstract

Uncertainty and indeterminacy are central concepts in economic policy design. The
inherent uncertainty is difficult to incorporate into traditional statistical models. To overcome the
limitation of classical inverse Gaussian (IG) distribution for managing the imprecise data, we
examine the structure of neutrosophic inverse Gaussian distribution (NIGD) which is an expansion
of the classical IG distribution under neutrosophic framework. The IG distribution, which is
commonly employed for reliability analysis and in financial modeling, features a positively skewed
curve which makes it is an appropriate index for modeling asymmetric economic data, including
risk assessments, investment returns, as well as financial duration. That model includes degrees of
truth, lack of information and degrees of falsity, elements that enable policymakers to compute
economic variables with incomplete / imprecise information. The mean, variance, skewness and
kurtosis of NIGD are derived in neutrosophic environment. The quantile function of the proposed
is derived which is further utilized to generate random samples from the proposed model. The
utilization of the distribution in economic uncertainty modeling is described using two numerical
examples.

DOI: 10.5281/zenodo.15009433