3 resultados para size-extensivity error

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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In 1999 Stephen Gorard published an article in this journal in which he provided a trenchant critique of what he termed the `politician's error' in analysing differences in educational attainment. The main consequence of this error, he argued, has been the production of misleading findings in relation to trends in educational performance over time that have, in turn, led to misguided and potentially damaging policy interventions. By using gender differences in educational attainment as a case study, this article begins by showing how Gorard's notion of the politician's error has been largely embraced and adopted uncritically by those within the field. However, the article goes on to demonstrate how Gorard's own preferred way of analysing such differences – by calculating and comparing proportionate changes in performance between groups – is also inherently problematic and can lead to the production of equally misleading findings. The article will argue that there is a need to develop a more reliable and valid way of measuring trends in educational performance over time and will show that one of the simplest ways of doing this is to make use of existing, and widely accepted, measures of effect size.

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For some time there is a large interest in variable step-size methods for adaptive filtering. Recently, a few stochastic gradient algorithms have been proposed, which are based on cost functions that have exponential dependence on the chosen error. However, we have experienced that the cost function based on exponential of the squared error does not always satisfactorily converge. In this paper we modify this cost function in order to improve the convergence of exponentiated cost function and the novel ECVSS (exponentiated convex variable step-size) stochastic gradient algorithm is obtained. The proposed technique has attractive properties in both stationary and abrupt-change situations. (C) 2010 Elsevier B.V. All rights reserved.

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Microsatellite genotyping is a common DNA characterization technique in population, ecological and evolutionary genetics research. Since different alleles are sized relative to internal size-standards, different laboratories must calibrate and standardize allelic designations when exchanging data. This interchange of microsatellite data can often prove problematic. Here, 16 microsatellite loci were calibrated and standardized for the Atlantic salmon, Salmo salar, across 12 laboratories. Although inconsistencies were observed, particularly due to differences between migration of DNA fragments and actual allelic size ('size shifts'), inter-laboratory calibration was successful. Standardization also allowed an assessment of the degree and partitioning of genotyping error. Notably, the global allelic error rate was reduced from 0.05 ± 0.01 prior to calibration to 0.01 ± 0.002 post-calibration. Most errors were found to occur during analysis (i.e. when size-calling alleles; the mean proportion of all errors that were analytical errors across loci was 0.58 after calibration). No evidence was found of an association between the degree of error and allelic size range of a locus, number of alleles, nor repeat type, nor was there evidence that genotyping errors were more prevalent when a laboratory analyzed samples outside of the usual geographic area they encounter. The microsatellite calibration between laboratories presented here will be especially important for genetic assignment of marine-caught Atlantic salmon, enabling analysis of marine mortality, a major factor in the observed declines of this highly valued species.