Abstract:
In this article, we introduce a new family of lifetime distributions with one extra
shape parameter, called the Amoud-G family, based on the cumulative hazard rate
function, the well-known concept in survival and reliability analysis. Some funda-
mental theoretical properties of the new family including cumulative hazard func-
tion, hazard rate, retro hazard, distribution function, quantile function, residual life
function, moments, entropy, among others are derived. A special case of this new
family is introduced by considering Weibull distribution as the baseline distribution
called Amoud-Weibull distribution. The model parameters of the Amoud-Weibull
distribution are estimated using the maximum likelihood estimation technique. The
proposed distribution is used to introduce a new accelerated failure time model,
which has been used to produce estimations of its model parameters. The perfor-
mance of the estimation approach based on the Amoud-Weibull distribution and
its hazard-based regression modeling has been examined using Monte Carlo sim-
ulation analysis. In addition, four examples of real-life data sets with complete
and right-censored observations are examined to show the utility and superiority
of the newly proposed distribution over other fundamental distributions and their
hazard-based regression models in terms of the baseline Weibull distribution and its
accelerated failure time model. Finally, the empirical results show that the proposed
family of survival distributions provides more realistic fits than other well-known
families in terms of complete and right-censored observations..
