Author

• A. A. Olosunde

Abstract

Abstract. In this paper, we propose to study a generalized form of the exponential power distribution which contains others in the literature
as special cases. This unifying exponential power distribution is characterized
by a parameter ω and a function h(ω) which regulates the tail
behavior of the distribution, thus making it more flexible and suitable
for modeling than the usual normal distribution, while retaining symmetry.
We derive several mathematical and statistical properties of this
distribution and estimate the parameters using both the moments and
maximum likelihood approach, obtaining the information matrix in the
process. The multivariate extension of the distribution is also examined.
Finally we fit the univariate generalized exponential power distribution
as well as the normal distribution to data on eggs produced by chicken
on each of two different poultry feeds (inorganic and organic copper-salt
compositions) and show that the generalized exponential power distribution
fit is considerably better. We then use the Kolmogorov-Smirnov
two samples one-tailed test to show that there is an increase in egg
weights and decrease in cholesterol level when the feed is organic.

Keywords

• Exponential power distribution
• information matrix
• inorganic copper-salt
• Maximum likelihood estimation
• multivariate exponential power distribution
• organic copper-salt
• poultry feeds data