Susam, Selim Orhun

This study develops the method of constructing a multi-parametric distribution on the unit interval using Bernstein polynomials and investigates its key statistical properties. The performance of the proposed distribution’s parameter estimators was evaluated by Monte Carlo simulation under both maximum-likelihood (MLE) and minimum-distance frameworks, with the MLE approach generally yielding lower estimation error. A real data example illustrates the advantages of the construction method. The results reveal that the Bernstein distribution provides superior goodness-of-fit to the dataset compared with competing models.

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Susam, Selim Orhun; Hudaverdi, Burcu

In this paper, we study on improving the goodness-of fit for the data by using τ-preserving transform for the semiparametric family of bivariate copulas. We estimate the generator function (Formula presented.) using the Bézier polynomial function and define τ- preserving transformation on the generator function under positive quadrant dependence assumption. We investigate the performance of our methodology on real data example contained life expectancy study. The findings indicate that the model fitting is improved by using τ- preserving transformation.

AtıfScopus3·WoS3·OpenAlex2

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