Garima Distribution and its Application to Model Behavioral Science Data
Rama Shanker · Biometrics & Biostatistics International Journal · 2016
In this paper a continuous distribution named "Garima distribution" has been suggested for modeling data from behavioral science.The important properties including its shape, moments, skewness, kurtosis, hazard rate function, mean residual life function, stochastic ordering, mean deviations, order statistics, Bonferroni and Lorenz curves, entropy measure, stress-strength reliability have been discussed.The condition under which Garima distribution is over-dispersed, equi-dispersed, and under-dispersed are presented along with other one parameter continuous distributions.The estimation of its parameter has been discussed using maximum likelihood estimation and method of moments.The application of the proposed distribution has been explained using a numerical example from behavioral science and the fit has been compared with other one parameter continuous distributions.