Let X denote the mean of a consecutive sequence of length n from an autoregression or moving average process. Suppose the covariance function of the process is regularly varying with exponent -[alpha], where [alpha] [greater-or-equal, slanted] 0. We show that the rate of convergence in a central...

A necessary and sufficient condition is given for busy period in an M/G/[infinity] queue to be asymptotically exponential with mean equal to expected busy period, as traffic intensity increases. The case where this condition fails is also investigated, and the results applied.

type="main" xml:id="rssb12067-abs-0001" <title type="main">Summary</title> <p>Errors-in-variables regression is important in many areas of science and social science, e.g. in economics where it is often a feature of hedonic models, in environmental science where air quality indices are measured with error, in biology where...</p>

type="main" xml:id="rssb12051-abs-0001" <title type="main">Summary</title> <p>We introduce a new method for improving the coverage accuracy of confidence intervals for means of lattice distributions. The technique can be applied very generally to enhance existing approaches, although we consider it in greatest detail in the...</p>

The Handbook on the Economics of Conflict conveys how economics can contribute to the understanding of conflict in its various dimensions embracing world wars, regional conflicts, terrorism and the role of peacekeeping in conflict prevention.

We develop a general methodology for tilting time series data. Attention is focused on a large class of regression problems, where errors are expressed through autoregressive processes. The class has a range of important applications and in the context of our work may be used to illustrate the...

In components of variance models the data are viewed as arising through a sum of two random variables, representing between- and within-group variation, respectively. The former is generally interpreted as a group effect, and the latter as error. It is assumed that these variables are...

Motivated by prediction problems for time series with heavy-tailed marginal distributions, we consider methods based on `local least absolute deviations' for estimating a regression median from dependent data. Unlike more conventional `local median' methods, which are in effect based on locally...

ARCH and GARCH models directly address the dependency of conditional second moments, and have proved particularly valuable in modelling processes where a relatively large degree of fluctuation is present. These include financial time series, which can be particularly heavy tailed. However,...