Most methods for finding interesting gene expression profiles from gene microarray data are based on a single discriminant, e.g. the classical paired t-test. Here a different approach is introduced based on gene ranking according to Pareto depth in multiple discriminants. The novelty of our approach, which is an extension of our previous work on Pareto front analysis (PFA), is that a gene’s rel...

Recent radar research interests in the Pareto distribution as a model for X-band maritime surveillance radar clutter returns have resulted in analysis of the asymptotic behaviour of this clutter model. In particular, it is of interest to understand when the Pareto distribution is well approximated by an Exponential distribution. The justification for this is that under the latter clutter model ...

Generalized linear models might not be appropriate when the probability of extreme events is higher than that implied by the normal distribution. Extending the method for estimating the parameters of a double Pareto lognormal distribution (DPLN) in Reed and Jorgensen (2004), we develop an EM algorithm for the heavy-tailed Double-Pareto-lognormal generalized linear model. The DPLN distribution i...

Abstract. Aksomaitis and Burauskaite-Harju [Information Technology and Control, 38, 2009, 301-302] studied the distribution of max(X1, X2,..., Xp) when (X1, X2,..., Xp) follows the multivariate normal distribution. Here, we study the moments of min(X1, X2,..., Xp) and max(X1, X2,..., Xp) when (X1, X2,..., Xp) follows the most commonly known multivariate Pareto distribution. Multivariate Pareto ...

The Pareto distribution is a simple model for nonnegative data with a power law probability tail. In many practical applications, there is a natural upper bound that truncates the probability tail. This paper derives estimators for the truncated Pareto distribution, investigates their properties, and illustrates a way to check for fit. We illustrate these methods with applications from finance,...

The weighted sum method of vector objective scalarization is known to generate points on convex Pareto front whose distribution cannot be controlled. This work presents a method of improving the distribution of Pareto points generated by weighted sum method by nonlinear weight selection. Numerical examples are presented to show the effectiveness of the method.

In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archive...

Distributional properties of min (X, Y ) and max(X, Y ) are studied when (X, Y ) has a bivariate Pareto distribution. Extensions are given to the multivariate case.

If business firms face a multiplicative growth process in which their growth rates are independent from their sizes, then these sizes cannot be distributed according to a stationary Pareto distribution. At the same time , the Laplace distribution of growth rates cannot be easily reconciled with a Pareto distribution of firm sizes. Recent contributions, using formal arguments, seems to contrast ...