Motivated by hydrological applications, we derive the exact distributions of R=X + Y, P=XY and W=X/(X+Y) and the corresponding moment properties when X and Y follow Friday and Patil's bivariate exponential distribution. An application of the results is provided to drought data from Nebraska....

The limiting distributions of the extremes of mixed exponential distributions and the associated rates of convergence are derived. The practical values of the results are illustrated by a numerical study.

An alternative inverse Gaussian distribution expressed in terms of the Bessel function is introduced. Both theoretical and empirical motivation is provided. Various particular cases and expressions for moments are derived. Estimation procedures by the method of moments and the method of maximum...

Downton’s bivariate exponential distribution has been a popular model for hydrological sciences. However, it seems that no explicit expressions for its product moments are available. In this short note, we provide a direct derivation of a general expression for the product moments and also...

We show that the correlation between the estimates of two parameters is almost unchanged if they are each transformed in an arbitrary way. To be more specific, the correlation of two estimates is invariant (except for a possible sign change) up to a first order approximation, to smooth...

A review is given of the exponentiated Weibull distribution, the first generalization of the two-parameter Weibull distribution to accommodate nonmonotone hazard rates. The properties reviewed include: moments, order statistics, characterizations, generalizations and related distributions,...

Many if not most lifetime distributions are motivated only by mathematical interest. Here, a new three-parameter distribution motivated mainly by lifetime issues is introduced. Some properties of the new distribution including estimation procedures, univariate generalizations and bivariate...

We give expressions for the distribution and density of a product of gamma or equivalently chi-square random variables. In particular, we give the distribution of the product of two independent gamma variables of mean k in terms of the Bessel functions K <Subscript>1</Subscript>, … , K <Subscript> k </Subscript>. Copyright Springer...</subscript></subscript>

Historically, the normal variance model has been used to describe stock return distributions. This model is based on taking the conditional stock return distribution to be normal with its variance itself being a random variable. The form of the actual stock return distribution will depend on...