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Conventional geostatistical methodology solves the problem of predicting the re-alised value of a linear functional of a Gaussian spatial stochastic process, S(x), based on observations Y i = S(x i) + Z i at sampling locations x i , where the Z i are mutually independent, zero-mean Gaussian random variables. We describe two spatial applications for which(More)
SUMMARY We propose a multivariate extreme value threshold model for joint tail estimation which overcomes the problems encountered with existing techniques when the variables are near independence. We examine inference under the model and develop tests for independence of extremes of the marginal variables, both when the thresholds are fixed, and when they(More)
for helpful comments. We are grateful to the referee and the editor for their comments and suggestions that result in a substantial improvement of this manuscript. Abstract This paper presents a general framework for identifying and modelling joint-tail distribution based on multivariate extreme value theories. We argue that the multivariate approach is the(More)
AIM To investigate the effectiveness of the Royal College of Radiologists Audit Sub-Committee's national prospective registry of percutaneous nephrostomy, which enables participants to audit their practice and compare performance with predetermined standards. METHODS Following a limited retrospective audit, which permitted setting of achievable targets, a(More)
OBJECTIVES To determine the clinical outcome of subintimal angioplasty (SA) and to assess impact on surgical workload. DESIGN Retrospective review of a single radiologist's case series. MATERIALS One hundred and twenty two patients with critical limb ischaemia and 26 with claudication. METHODS One hundred and fifty eight limbs treated by SA. MAIN(More)
In this paper we propose a new particle smoother that has a computational complexity of O(N), where N is the number of particles. This compares favourably with the O(N 2) computational cost of most smoothers and will result in faster rates of convergence for fixed computational cost. The new method also overcomes some of the degeneracy problems we identify(More)
Smith and Weissman introduced a M4 class of processes which are very flexible models for temporally dependent multivariate extreme value processes. However all variables in these M4 models are asymptotically dependent and what this paper does is to extend this M4 class in a number of ways to produce classes of models which are also asymptotically(More)