Recursive formulas for aggregate claim distributions
Regular Simplices and Gaussian Samples.
Relations for characteristic functions of k-th record values from generalized Pareto and inverse generalized Pareto distribution
Relations for the marginal, joint, conditional characteristic functions of k-th upper and lower record values from generalized Pareto distribution and inverse generalized Pareto distribution are given.
Relative increments of Pearson distributions.
Reproducibility in the One-Parameter Exponential Family.
Sample -copula of order
In this paper we analyze the construction of -copulas including the ideas of Cuculescu and Theodorescu [5], Fredricks et al. [15], Mikusiński and Taylor [25] and Trutschnig and Fernández-Sánchez [33]. Some of these methods use iterative procedures to construct copulas with fractal supports. The main part of this paper is given in Section 3, where we introduce the sample -copula of order with , the central idea is to use the above methodologies to construct a new copula based on a sample. The...
Sample Size, Parameter Rates and Contiguity - The i.n.n.i.d. Case
Selective lack-of-memory and its application
We say that a random variable X taking nonnegative integers has selective lack-of-memory (SLM) property with selector s if P(X ≥ n + s/X ≥ n) = P(X ≥ s) for n = 0,1,.... This property is characterized in an elementary manner by probabilities pₙ = P(X=n). An application in car insurance is presented.
Self-decomposable probability distributions on
Seules les affinités préservent le type de la loi gamma à paramètre entier
Sharp bounds on quasiconvex moments of generalized order statistics.
Shuffles of Min.
Copulas are functions which join the margins to produce a joint distribution function. A special class of copulas called shuffles of Min is shown to be dense in the collection of all copulas. Each shuffle of Min is interpreted probabilistically. Using the above-mentioned results, it is proved that the joint distribution of any two continuously distributed random variables X and Y can be approximated uniformly, arbitrarily closely by the joint distribution of another pair X* and Y* each of which...
Some Characterizations of Distributions by Regression Models for Ordinal Response Data.
Some Characterizations of the Bivariate Normal Distribution.
Some new functional equations connected with characterization problems.
Some notes on Rayleigh dirstribution
Some relationships between the generalized Gumbel and other distributions
Some results on the ageing class
Stability of a characterization of normal distributions based on the first two conditional moments.
Stability of characterizations of distribution functions using failure rate functions
Let denote the failure rate function of the . and let denote the failure rate function of the mean residual life distribution. In this paper we characterize the distribution functions for which and we estimate when it is only known that or is bounded.