26,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 6-10 Tagen
  • Broschiertes Buch

A new family of continuous probability distributions called Exponential-Gamma-X was generated from transforming a newly developed continuous probability distribution named Exponential-Gamma distribution. The newly developed Exponential-Gamma was studied and expressions for its statistical properties were also derived. The method of maximum likelihood was used to estimate the shape and the scale parameters of the distribution. The newly developed distribution was compared with existing probability distributions such as Exponential and Gamma distributions by applying it to four real life data in…mehr

Produktbeschreibung
A new family of continuous probability distributions called Exponential-Gamma-X was generated from transforming a newly developed continuous probability distribution named Exponential-Gamma distribution. The newly developed Exponential-Gamma was studied and expressions for its statistical properties were also derived. The method of maximum likelihood was used to estimate the shape and the scale parameters of the distribution. The newly developed distribution was compared with existing probability distributions such as Exponential and Gamma distributions by applying it to four real life data in order to illustrate its efficiency and flexibility. The results showed that the newly developed distribution for all the data sets were skewed to the right while the distribution behaves differently in term of the kurtosis, also the results obtained for all the data sets used showed that the newly developed distribution performed better than the existing distributions. Finally, the newly developed probability distribution was transformed to a T-X family of continuous distributions called Exponential-Gamma-X family of distributions thereby generalizing a new family of distribution.
Autorenporträt
Taiwo Michael Ayeni obtained his B.Sc. and M.Sc. in Statistics at the Ekiti State University Ado-Ekiti, Nigeria. He research and specializes in Probability Theory and Distributions.