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 …

Fuzzy regression analysis is aimed at modeling the relationship between a set of fuzzy
responses and a set of non-fuzzy/fuzzy predictors. However, compared to parametric …

In this paper, a new method is proposed for estimating fuzzy regression models based on a
novel robust support vector machines with exact predictors and fuzzy responses. For this …

There is a growing interest in the insurance industry in offering substandard annuities.
These annuities, based on medical underwriting, provide a greater pay out than the …

Spline smoothing is a form of nonlinear regression when there is reason to believe that
relationship between the predictor and the response is curvilinear. In such cases, the spline …

Quantile regression estimates conditional quantiles and has found extensive applications in
real-life statistical procedures. This study assessed a new for nonlinear quantile regression …

Abstract The Lee—Carter model is a useful dynamic stochastic model to represent the
evolution of central mortality rates throughout time. This model only considers the …

Deviations in port container handling can be detected by many factors. One of them is
anomalies in the process model. Several studies have proposed anomaly detection …

El estudio tuvo como objetivo proponer un nuevo enfoque para el método chain-ladder
mediante el uso de Números Fuzzy Gaussianos. Por tanto, el texto introduce conceptos y …

This paper proposed an extension for the classical partial univariate regression model with
non-fuzzy inputs and triangular fuzzy output. For this purpose, the popular non-parametric …