During mathematical modeling of real technical system we can meet any type and rate model uncertainty. Its reasons can be incognizance of modelers or data inaccuracy. So, classification of uncertainties, with respect to their sources, distinguishes between aleatory and epistemic ones. The aleatory uncertainty is an inherent data variation associated with the investigated system or its environment. Epistemic one is an uncertainty that is due to a lack of knowledge of quantities or processes of the system or the environment. In this short communication, we discuss quadruple neutrosophic numbers and their potential application for realistic modelling of physical systems, especially in the reliability assessment of engineering structures.
Authors: Hazhir Homei
Comments: 5 Pages.
It has been stated in the literature that for finding uniformly minimum-variance unbiased estimator through the theorems of Rao-Blackwell and Lehmann-Scheffe, the sufficient statistic should be complete; otherwise the discussion and the way of finding uniformly minimum-variance unbiased estimator should be changed, since the sufficiency assumption in the Rao-Blackwell and Lehmann-Scheffe theorems limits its applicability. So, it seems that the sufficiency assumptions should be expressed in a way that the uniformly minimum-variance unbiased estimator be derivable via the Rao-Blackwell and Lehmann-Scheffe theorems.