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Skellam's name is traditionally attached to the distribution of the difference of two independent Poisson random variables. Many bivariate extensions of this distribution are possible, e.g., through copulas. In this paper, the authors focus on a probabilistic construction in which two Skellam random variables are affected by a common shock. Two different bivariate extensions of the Skellam distribution stem from this construction, depending on whether the shock follows a Poisson or a Skellam distribution. The models are nested, easy to interpret, and yield positive quadrant-dependent distributions, which share the convolution closure property of the univariate Skellam distribution. The models can also be adapted readily to account for negative dependence. Closed form expressions for Pearson's correlation between the components make it simple to estimate the para-meters via the method of moments. More complex formulas for Kendall's tau and Spearman's rho are also provided. [ABSTRACT FROM PUBLISHER]

Abstract: Let be a random sample from an absolutely continuous distribution with non-negative support, and let be mutually independent lifetimes with proportional hazard rates. Let also and be their associated order statistics. It is shown that the pair is then more dependent than the pair , in the sense of the right-tail increasing ordering of Avérous and Dortet-Bernadet [LTD and RTI dependence orderings, Canad. J. Statist. 28 (2000) 151–157]. Elementary consequences of this fact are highlighted. [Copyright &y& Elsevier]

A preface for the volume 33, number 3, 2005 of "The Canadian Journal of Statistics" is presented.

A formula is given for the statistic that provides the locally most powerful rank test of independence against alternatives expressed by copula models. The Savage, Spearman and van der Waerden statistics are seen to be optimal in special cases of interest. The asymptotic relative efficiency (ARE) of any linear rank procedure with respect to the optimal test is expressed as a squared correlation in which the bivariate dependence structure of the data only enters through the copula. In contrast, the margins are shown to influence the ARE of the best rank test, compared to the standard test of independence based on Pearson’s correlation. An extensive simulation study is used to assess the effect of both the margins and the dependence structure on the power of several parametric and nonparametric procedures in small samples from a variety of bivariate distributions. [ABSTRACT FROM AUTHOR]

Deux versions d'un paradoxe statistique ayant trait à un certain 'principe d'ancillarité' ont récemment été proposées par Godambe (1979, 1982). Dans cette note, nous montrons que les deux versions de son paradoxe sont en fait d'une nature totalement différente et nous les résolvons toutes les deux en les examinant à la lumière du concept de répartition aléatoire. La première version du paradoxe de Godambe a déja été critiquée par Good (1980), mais nous croyons que son argumentation est défaillante. [ABSTRACT FROM AUTHOR]

The article discusses the combination of a number of opinions that have been expressed as probability measures P1, ..., Pn over some space. It is stated that a pooling formula with the marginalization property must be in the expression T=En1_w1P1 + (1 - E1_w1)Q. It presents a theorem that characterizes those pooling operators which have marginalization property.

One of the building blocks of the Analytic Hierarchy Process (Saaty 1977) is the ratio-scaled assessment of an agent's preferences between pairs of alternatives. This article shows how it is possible to visualize such data and to detect cardinal and ordinal inconsistencies in the respondent's judgments. The graphical method used to display preferences is not new in itself: it dates back at least to the work of Gower (1977), and many variants of his technique can be found in the literature. But Gower plots provide an especially valuable diagnostic tool in the context of AHP, as discussed and abundantly illustrated herein. [ABSTRACT FROM AUTHOR]

The article presents a report from the editor of "The Canadian Journal of Statistics" with regards to the number of submissions to the journal in 1998, the distribution of time elapsed between the receipt of the manuscript submitted and the dispatch of a first decision, as well as the new members of the editorial board.