In this paper we tackle the problem of estimating the power-law tail exponent of income distributions by using the Hill’s estimator. A subsample semi-parametric bootstrap procedure minimizing the mean squared error is used to choose the power-law cutoff value optimally. This technique is applied to personal income data for Australia and Italy. r 2006 Elsevier B.V. All rights reserved.

BACKGROUND As a result of reporting bias, or frauds, false or misunderstood findings may represent the majority of published research claims. This article provides simple methods that might help to appraise the quality of the reporting of randomized, controlled trials (RCT). METHODS This evaluation roadmap proposed herein relies on four steps: evaluation of the distribution of the reported va...

Two-dimensional Monte Carlo simulation can be used to estimate the variability and uncertainty of emissions of urban air toxics for use in human exposure and risk analysis. The key steps in the twodimensional approach include fitting a parametric distribution to data representing variability in emissions, and to use a method such as bootstrap simulation to estimate uncertainty in average emissi...

The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one’s data or a model estimated from the data. The methods that are available for implementing the bootstrap and the accuracy of bootstrap estimates depend on whether the data are a random sample from a distribution or a time series. This paper is concerned with the application of the boots...