Beta Weighted Exponential Distribution: Theory and Application

[10] modified the idea of [2] in which they introduced a shape parameter to an exponential model toobtain the weighted exponential distribution. In this article, we introduced two shape parameters to the existing weighted exponential distribution to develop the beta weighted exponential distribution using the logit of beta function by [12]. We studied the statistical properties of the new distribution. Parameter estimation was done by the method of maximum likelihood estimation with R software code. We then used a data set on survival times of guinea pigs injected with different amount of tubercle bacilli to compare properties of well-known distributions with those ofthe new distribution. Our comparison showed the new distribution as the much more flexible and versatile