This monograph examines the domain of classical political economy using the methodologies developed in recent years both by the new discipline of econo-physics and by computing science. This approach is used to re-examine the classical subdivisions of political economy: production, exchange,...

During periods of market stress, electricity prices can rise dramatically. This paper treats these abnormal episodes or price spikes as count events and attempts to build a model of the spiking process. By contrast to the existing literature, which either ignores temporal dependence in the...

Motivated by examples in spectroscopy, we study variable selection for discrimination in problems with very many predictor variables. Assuming multivariate normal distributions with common variance for the predictor variables within groups, we develop a Bayesian decision theory approach that...

There are few techniques available for testing whether or not a family of parametric times series models fits a set of data reasonably well without serious restrictions on the forms of alternative models. In this paper, we consider generalised likelihood ratio tests of whether or not the...

Likelihood ratio theory has had tremendous success in parametric inference, due to the fundamental theory of Wilks. Yet, there is no general applicable approach for nonparametric inferences based on function estimation. Maximum likelihood ratio test statistics in general may not exist in...

The empirical likelihood cannot be used directly sometimes when an infinite dimensional parameter of interest is involved. To overcome this difficulty, the sieve empirical likelihoods are introduced in this paper. Based on the sieve empirical likelihoods, a unified procedure is developed for...

Although diarrhoea and malaria are among the leading causes of child mortality and morbidity in Sub-Saharan Africa, few detailed studies have examined the patterns and determinants of these ailments in the most affected communities. In this paper, we investigate the spatial clustering of...

We develop a new class of prior distributions for Bayesian comparison of nested models, which we call intrinsic moment priors, by combining the well-established notion of intrinsic prior with the recently introduced idea of non-local priors, and in particular of moment priors. Specifically, we...

We consider the assessment of disclosure risk in the release of microdata from social surveys as public-use files. We consider both identification risk and the notion of differential privacy introduced in the computer science literature. We show that sampling, as a disclosure limitation...

Business surveys often use complex sets of edit rules (edits, for short) to check returned questionnaires (records), locate suspicious or unacceptable responses, and support data cleaning operations prior to using the survey responses for estimation of the required target parameters. These sets...