Conjugate processes and the silumation of ruin problems

AbstractA general methods is developed for giving simulation estimates of boundary crossing probabilities for processes related to random walks in discreate or continuous time. Particular attention is given to the probability ψ(u, T of ruin before time T in cpumpound Poisson risk processes. When the provbabi;ity law P governing the given process is imbedded in an exponentaial family (Pgq), one can write ψ (u, T) + θRgq for certain random variables Rgq given by Wald's fundamental identity. Using this to simulate from Pgq rather than P, it is possible not only to overcome the difficulties connected with the case T =∞, but also to obtain a considerable variance reduction.It is shown that the solution of the Lundberg equation determines the asymptotically optimal value of θ in heavy traffic when T = ∞, and some results guidelining the choice of θ when T > ∞ are also given. The potential of the method in different is illustrated by two examples

Spatial electron density and electric field strength measurements in microwave cavity experiments

Measurements of electron density and electric field strength have been made in an argon plasma contained in a resonant microwave cavity at 2.45 GHz. Spatial measurements of electron density, n sub e, are correlated with fluorescence observations of the discharge. Measurements of n sub e were made with Stark broadening and compared with n sub 3 calculated from measured plasma conductivity. Additional measurements of n sub 3 as a function of pressure and in mixtures of argon and oxygen are presented for pressures from 10 Torr to 1 atm. Measurements in flowing gases and in static systems are presented. In addition, limitations of these measurements are identified

Reading In Families: A Research Update

Asmussen and Gaffney have uncovered one of the many rich sources of research data inherent in the Read ing Recovery program. The Ohio research studies (already some 13 volumes) have documented the success of Reading Recovery in the United States. Success like this produces a need to unravel the warp and woof to examine the nature of that success. Certainly there are many threads to examine. In this brief research update, they describe a current study to explore reading in the families of a sample of Reading Recovery children in Illinois. It will be interesting to compare their findings with Kathleen Holland\u27s stimulating research exploring the parent and home literacy context of 13 Ohio Reading Recovery children in 1986-87, case studies conducted when Reading Recovery was in its infancy in the US. The Asmussen and Gaffney study explores the important dynamics of becoming literate at a time when Americans have more knowledge of Reading Recovery and a need to understand its impact on family literacy

Tail asymptotics for dependent subexponential differences

We study the asymptotic behavior of ℙ(X − Y > u) as u → ∞, where X is subexponential, Y is positive, and the random variables X and Y may be dependent. We give criteria under which the subtraction of Y does not change the tail behavior of X. It is also studied under which conditions the comonotonic copula represents the worst-case scenario for the asymptotic behavior in the sense of minimizing the tail of X − Y. Some explicit construction of the worst-case copula is provided in other case

Tail asymptotics for dependent subexponential differences

We study the asymptotic behavior of ℙ(X − Y > u) as u → ∞, where X is subexponential, Y is positive, and the random variables X and Y may be dependent. We give criteria under which the subtraction of Y does not change the tail behavior of X. It is also studied under which conditions the comonotonic copula represents the worst-case scenario for the asymptotic behavior in the sense of minimizing the tail of X − Y. Some explicit construction of the worst-case copula is provided in other cases

Heavy Tails, Importance Sampling and Cross-Entropy

We consider the problem of estimating P (Y1+ ... +Yn > x) by importance sampling when the Yi are i.i.d. and heavy-tailed. The idea is to exploit the cross-entropy method as a tool for choosing good parameters in the importance sampling distribution; in doing so, we use the asymptotic description that given P(Y1+ ... +Yn > x,) n-1 of the Yi have distribution F and one the conditional distribution of Y given Y > x. We show in some parametric examples (Pareto and Weibull) how this leads to precise answers, which as demonstrated numerically, are close to being variance minimal within the parametric class under consideration. Related problems for M/G/1 and GI/G/1 queues are also discussed