Statistical regression analysis is a powerful and reliable method to determine the impact of
one or several independent variable (s) on a dependent variable. It is the most widely used …

This paper makes a systematic bibliographical analysis of the contributions of fuzzy set
theory (FST) on option pricing to state principal mainstream focuses and exposes the basic …

Existing literature asserts that the growth of life settlement (LS) markets, where they exist, is
hampered by limited policyholder participation and suggests that to foster this growth …

The insurance industry has numerous areas with potential applications for fuzzy logic (FL).
These include classification, underwriting, projected liabilities, fuzzy future and present …

Individuals may have difficulty in determining whether or not to buy insurance against low‐
probability, high‐loss events. This ambivalence would cause preference uncertainty and …

In a great deal of literature on fuzzy regression analysis, most of research has focused on
some predefined parametric forms of fuzzy regression relationships, especially on the fuzzy …

Solid bulk cargoes transported by dry/bulk cargo ships pose notable fire and safety risks.
Such ships are equipped with fixed fire extinguishing systems that are meant to help fight …

In this paper, a fuzzy formulation of the Lee–Carter [Lee, RD, Carter, LR, 1992. Modeling
and forecasting US mortality. J. Amer. Statist. Assoc. 419 (87), 659–675] model is proposed …

Regression analysis is a quantitative research tool that is used to model and analyse
multiple variables in a dependent-independent relationship in order to create the most …

Fuzzy regression models have been applied to operational research (OR) applications such
as forecasting. Some of previous studies on fuzzy regression analysis obtain crisp …