Stathis Chadjiconstantinidis

Joint distributions of successes, failures and patterns in enumeration problems

Let ε be a (single or composite) pattern defined over a sequence of Bernoulli trials. This article presents a unified approach for the study of the joint distribution of the number S n of successes (and F n of failures) and the number X n of occurrences of ε in a fixed number of trials as well as the joint distribution of the waiting time T r till the rth occurrence of the pattern and the number S T r of successes (and F T r of failures) observed at that time. General formulae are developed for the joint probability mass functions and generating functions of (X n ,S n ), (T r ,S T r ) (and (X n ,S n ,F n ),(T r ,S T r ,F T r )) when X n belongs to the family of Markov chain imbeddable variables of binomial type. Specializing to certain success runs, scans and pattern problems several well-known results are delivered as special cases of the general theory along with some new results that have not appeared in the statistical literature before.

Measures of component importance for Markov chain imbeddable reliability structures

In this article we study the reliability importance of the components for the wide class of Markov chain imbeddable systems (MIS). Methods for the evaluation of Birnbaum importance are developed for a general MIS, and some generating function techniques are demonstrated for the special case of homogeneous MISs. As an application, the reliability ordering for the components of a k-out-of-n and consecutive-k-out-of-n structure is examined in some detail.

On Mixed and Compound Mixed Poisson Distributions

Recursive formulae are derived for the evaluation of the t-th order cumulative distribution function and the t-th order tail probability of compound mixed Poisson distributions in the case where the derivative of the logarithm of the mixing density can be written as a ratio of polynomials. Also, some general results are derived for the evaluation of the t-th order moments of stop-loss transforms. The recursions can be applied for the exact evaluation of the probability function, distribution function, tail probability and stop-loss premium of compound mixed Poisson distributions and the corresponding mixed Poisson distributions. Several examples are also presented.

On a renewal risk process with dependence under a Farlie - Gumbel - Morgenstern copula

In this article, we consider an extension to the renewal or Sparre Andersen risk process by introducing a dependence structure between the claim sizes and the interclaim times through a Farlie–Gumbel–Morgenstern copula proposed by Cossette et al. (2010) for the classical compound Poisson risk model. We consider that the inter-arrival times follow the Erlang(n) distribution. By studying the roots of the generalised Lundberg equation, the Laplace transform (LT) of the expected discounted penalty function is derived and a detailed analysis of the Gerber–Shiu function is given when the initial surplus is zero. It is proved that this function satisfies a defective renewal equation and its solution is given through the compound geometric tail representation of the LT of the time to ruin. Explicit expressions for the discounted joint and marginal distribution functions of the surplus prior to the time of ruin and the deficit at the time of ruin are derived. Finally, for exponential claim sizes explicit expressions and numerical examples for the ruin probability and the LT of the time to ruin are given.

Moments of compound mixed Poisson distributions

Recursive formulae are derived for the evaluation of the moments and the descending factorial moments about a point n of mixed Poisson and compound mixed Poisson distributions, in the case where the derivative of the logarithm of the mixing density can be written as a ratio of polynomials. As byproduct, we also obtain recursive formulae for the evaluation of the moments about the origin, central moments, descending and ascending factorial moments of these distributions. Examples are also presented for a number of mixing densities.

On a perturbed by diffusion compound Poisson risk model with delayed claims and multi-layer dividend strategy

In this paper we consider an extension to the compound Poisson risk process perturbed by diffusion in which two types of dependent claims, main claims and by-claims, are incorporated. Every by-claim is induced by the main claim and may be delayed for one time period with a certain probability. An integro-differential equation system for the Gerber-Shiu expected discounted penalty functions is derived and solved by proving that the Gerber-Shiu function satisfies some defective renewal equation. An exact representation for the solution of this equation is derived through an associated compound geometric distribution and an analytic expression for this quantity is given when both the claim and the by-claim amounts belong to the rational family of distributions. Further, the same risk model is considered in the presence of a multi-layer dividend strategy. A system of integro-differential equations for the expected discounted penalty functions depending on the current surplus level, with certain initial and boundary conditions, is obtained. To solve this, we derive a general solution to a certain second order integro-differential equation system. This solution is obtained by transforming this system to a Volterra-type system of integral equations of second kind, which is solved by using Laplace transforms provided an explicit expression for the Gerber-Shiu functions depending on the current surplus level. Finally, numerical results for the ruin probability are given to illustrate the applicability of our results.

Non-exponential bounds for stop-loss premiums and ruin probabilities

We present an inventory of non-exponential bounds for ruin probabilities and stop-loss premiums in the general Sparre-Andersen model (renewal model) of risk theory. Various additional bounds are given if one assumes that the ladder height distribution F associated with the risk process belongs to a certain class of distributions, in particular if it is concave or it exhibits a (positive or negative) aging property. In most cases, these bounds are shown to improve existing ones in the literature and/or possess the correct asymptotic behaviour when the distribution F is subexponential. Since in the classical (compound Poisson) risk model the ladder height distribution is always concave, all the bounds given in the paper are also valid for this model. Finally, in many cases the results of the paper are also valid for any compound geometric distribution.

Distributions of the Numbers of Failures and Successes in a Waiting Time Problem

Abstract. In this article we consider infinite sequences of Bernoulli trials and study the exact and asymptotic distribution of the number of failures and the number of successes observed before the r-th appearance of a pair of successes separated by a pre-specified number of failures. Several formulae are provided for the probability mass function, probability generating function and moments of the distribution along with some asymptotic results and a Poisson limit theorem. A number of interesting applications in various areas of applied science are also discussed.