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A four-parameter family of Weibull distributions is introduced, as an example of a more general class created along the lines of Marshall and Olkin, 1997. Various properties of the distribution are explored and its usefulness in modelling real data is demonstrated using maximum likelihood estimates.

Primary renal lymphoma is a rare clinicopathologic entity that typically presents as renal mass or renal impairment with enlarged kidneys. We describe the case of a 66-year-old woman who presented with type II mixed cryoglobulinaemic vasculitis as the first manifestation of underlying low-grade primary renal lymphoma.

An EM algorithm is proposed for computing estimates of parameters of the negative binomial distribution; the algorithm does not involve further iterations in the M-step, in contrast with the one given in Schader & Schmid (1985). The approach can be applied to the corresponding problem in the logarithmic series distribution. The convergence of the proposed scheme is investigated by simulation, the observed Fisher information is derived and numerical examples based on real data are presented.