Lesson plan
Contour boxplot
In statistical graphics and scientific visualization, the contour boxplot is an exploratory tool that has been proposed for visualizing ensembles of feature-sets determined by a threshold on some scalar function (e.g. level-sets, isocontours). Analogous to the classical boxplot and considered an expansion of the concepts defining functional boxplot, the descriptive statistics of a contour boxplot are: the envelope of the 50% central region, the median curve and the maximum non-outlying envelope. To construct a contour boxplot, data ordering is the first step. In functional data analysis, each observation is a real function, therefore data ordering is different from the classical boxplot where scalar data are simply ordered from the smallest sample value to the largest. More generally, data depth, gives a center-outward ordering of data points, and thereby provides a mechanism for constructing rank statistics of various kinds of multidimensional data. For instance, functional data examples can be ordered using the method of band depth or a modified band depth. In contour data analysis, each observation is a feature-set (a subset of the domain), and therefore not a function. Thus, the notion of band depth and modified band depth is further extended to accommodate features that can be expressed as sets but not necessarily as functions.…
Article summary
In statistical graphics and scientific visualization, the contour boxplot is an exploratory tool that has been proposed for visualizing ensembles of feature-sets determined by a threshold on some scalar function (e.g. level-sets, isocontours). Analogous to the classical boxplot and considered an expansion of the concepts defining functional boxplot, the descriptive statistics of a contour boxplot are: the envelope of the 50% central region, the median curve and the maximum non-outlying envelope. To construct a contour boxplot, data ordering is the first step. In functional data analysis, each observation is a real function, therefore data ordering is different from the classical boxplot where scalar data are simply ordered from the smallest sample value to the largest. More generally, data depth, gives a center-outward ordering of data points, and thereby provides a mechanism for constructing rank statistics of various kinds of multidimensional data. For instance, functional data examples can be ordered using the method of band depth or a modified band depth. In contour data analysis, each observation is a feature-set (a subset of the domain), and therefore not a function. Thus, the notion of band depth and modified band depth is further extended to accommodate features that can be expressed as sets but not necessarily as functions.…
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Discussion questions
- Summarise the article in your own words. Which single claim would you verify first, and why?
- Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
- If two sources disagreed about one of these facts, what would you need in order to trust one over the other?
Bibliography
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Key claims and bibliography are generated from the same tracked claims and sources as the article page.