منابع مشابه
Visualizing Multiple Quantile Plots.
Multiple-quantile plots provide a powerful graphical method for comparing the distributions of two or more populations. This article develops a method of visualizing triple-quantile plots and their associated confidence tubes, thus extending the notion of a quantile-quantile (QQ) plot to three dimensions. More specifically, we consider three independent one-dimensional random samples with corre...
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The nonparametric empirical likelihood approach is used to obtain simultaneous confidence tubes for multiple quantile plots based on k independent (possibly right-censored) samples. These tubes are asymptotically distribution free, except when both k > 3 and censoring is present. Pointwise versions of the confidence tubes, however, are asymptotically distribution free in all cases. The various ...
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The nonparametric empirical likelihood approach is used to obtain simultaneous conndence tubes for multiple quantile plots based on k independent (possibly right-censored) samples. These tubes are asymptotically distribution-free, except when both k 3 and censoring is present. Pointwise versions of the conndence tubes, however, are asymptotically distribution-free in all cases. The various conn...
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In a previous article, we introduced a number of visualization techniques that we had developed for monitoring the dynamics of artificial competitive coevolutionary systems. One of these techniques involves evaluating the performance of an individual from the current population in a series of trials against opponents from all previous generations, and visualizing the results as a 2D grid of sha...
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Scatter plots are mostly used for correlation analysis, but are also a useful tool for understanding the distribution of high-dimensional point cloud data. An important characteristic of such distributions are clusters, and scatter plots have been used successfully to identify clusters in data. Another characteristic of point cloud data that has received less attention so far are regions that c...
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ژورنال
عنوان ژورنال: Journal of Computational and Graphical Statistics
سال: 2012
ISSN: 1061-8600,1537-2715
DOI: 10.1080/10618600.2012.680865