In this paper we consider a transportation system consisting of a carrier with capacity Q \le \infty , operating between two terminals. Passengers arrive at these terminals according to independent Poisson processes and are transported by the carrier from one terminal to the other terminal....

Recent advances in social science surveys include collection of biological samples. Although biomarkers offer a large potential for social science and economic research, they impose a number of statistical challenges, often being distributed asymmetrically with heavy tails. Using data from the...

In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient...

This paper seeks to identify computationally efficient importance sampling (IS) algorithms for estimating large deviation probabilities for the loss on a portfolio of loans. Related literature typically assumes that realised losses on defaulted loans can be predicted with certainty, i.e., that...

Fitting parametric models or the use of the empirical cumulative distribution function are problematic when it comes to the estimation of tail probabilities from small samples. A possible remedy is to fuse or combine the small samples with additional data from external sources and base the...

We show that the weak Pareto law, as used to characterize the tail behaviour of income distributions, implies regularly varying tail probabilities, but that the reverse implication does not hold. We also establish implications among other versions of the weak Pareto law.

In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient...

Fitting parametric models or the use of the empirical cumulative distribution function are problematic when it comes to the estimation of tail probabilities from small samples. A possible remedy is to fuse or combine the small samples with additional data from external sources and base the...

Recent advances in social science surveys include collection of biological samples. Although biomarkers offer a large potential for social science and economic research, they impose a number of statistical challenges, often being distributed asymmetrically with heavy tails. Using data from the...