Moderate deviations in subsampling distribution estimation

In Politis and Romano (1994) the subsampling methodology was put forth for approximating the sampling distribution (and the corresponding quantiles) of general statistics from i.i.d. and stationary data. In this note, we address the question of how well the subsampling distribution approximates the tail of the target distribution. In the regular setting of the sample mean of an -dependent sequence we show a moderate deviation property of the subsampling distribution.

     

Assessment of liver fat quantification in the presence of iron

This study assesses the stability of magnetic resonance liver fat measurements against changes in T2* due to the presence of iron, which is a confound for accurate quantification. The liver T2* was experimentally shortened by intravenous infusion of a super paramagnetic iron oxide contrast agent. Low flip angle multiecho gradient echo sequences were performed before, during and after infusion. The liver fat fraction (FF) was calculated in co-localized regions-of-interest using T2* models that assumed no decay, monoexponential decay and biexponential decay. Results show that, when T2* was neglected, there was a strong underestimation of FF and with monoexponential decay there was a weak overestimation of FF. Curve-fitting using the biexponential decay was found to be problematic. The overestimation of FF may be due to remaining deficiencies in the model, although is unlikely to be important for clinical diagnosis of steatosis.     

Linearisierung von Gruppendaten mit Anwendungen auf Knotengruppen

Ohne Zusammenfassung     

Kummer's lemma for cyclic 2-groups

For cyclic 2-groupsC, we characterize the kernel of the map induced on the units of the integral group ring by the coefficient reduction . This allows us to prove that, for any finite abelian 2-groupA, the circular units of ℤA (i.e. those which are mapped to cyclotomic units by every character ofA) can be generated in a certain systematic way. Work supported in part by an NSERC (Canada) operating grant     

A local search heuristic for the Multi-Commodity k-splittable Maximum Flow Problem

The Multi-Commodity $k$ -splittable Maximum Flow Problem consists of maximizing the amount of flow routed through a network such that each commodity uses at most $k$ paths and such that edge capacities are satisfied. The problem is $\mathcal NP $ -hard and has application in a.o. telecommunications. In this paper, a local search heuristic for solving the problem is proposed. The heuristic is an iterative shortest path procedure on a reduced graph combined with a local search procedure to modify certain path flows and prioritize the different commodities. The heuristic is tested on benchmark instances from the literature and solves 83 % of the instances to optimality. For the remaining instances, the heuristic finds good solution values which on average are 1.04 % from the optimal. The heuristic solves all instances in less than a second. Compared to other heuristics, the proposed heuristic again shows superior performance with respect to solution quality.