Nadarajah and Haghighi has defined the extension of the exponential distribution we have called this as NHE
distribution. It is continuous probability distribution with a wide range of applications such as in life testing experiments,
reliability analysis, applied statistics and clinical studies. However, it is not flexible enough for modeling heavily skewed datasets
as compared to modified distributions. In this study, we have generated a new continuous distribution having three parameters
based on the half logistic-Generating family called half logistic NHE. The structural properties of this model are explored such
as the probability density, cumulative density, hazard rate, reversed hazard rate, and quantile functions. The model parameters
are estimated using the three well-known methods namely maximum likelihood estimation (MLE), least-square estimation (LSE)
and Cramer-Von-Mises (CVM) methods. Further, we have computed the Fisher information matrix and asymptotic confidence
intervals for ML estimators.
