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Clustering is an important data exploration task. A prominent clustering algorithm is agglomerative hierarchical clustering. Roughly, in each iteration, it merges the closest pair of clusters. It was rst proposed way back in 1951, and since then there have been numerous mod-iications. Some of its good features are: a natural, simple, and non-parametric grouping of similar objects which is capab...

The plotting of cumulative sums (cusums), a technique of proven value in the detection of trends in data collected at intervals of time, may be modified to analyze circadian blood pressure patterns quantitatively. Mean 24-hour ambulatory blood pressure is taken as the reference value and is subtracted from each pressure value. The products of the remainders and the corresponding time intervals ...

We introduce a new visualization method for temporal data, Spiral Theme Plot, by combining ThemeRiver method, spiral patterns, and scatter plot technique. Similar to ThemeRiver, data in different categories (themes) are visualized in different bands, but also in a spiral pattern. Themes are stacked along a spiral curve, which represent the time axis. Individual data points are plotted within th...

The paper advocates the use of a statistical tool dedicated to the exploration of data samples populated by several sources of events. This new technique, called s Plot, is able to unfold the contributions of the different sources to the distribution of a data sample in a given variable. The s Plot tool applies in the context of a Likelihood fit which is performed on the data sample to determin...

This paper supplements a video clip submitted to the Video Track of IEEE Symposium on Information Visualization 2005. The original video submission applies a two-way storytelling approach to demonstrate the visual analytics capabilities of a new visualization technique. The paper presents our video production philosophy, describes the plot of the video, explains the rationale behind the plot, a...

The paper advocates the use of a statistical tool dedicated to the exploration of data samples populated by several sources of events. This new technique, called s Plot, is able to unfold the contributions of the different sources to the distribution of a data sample in a given variable. The s Plot tool applies in the context of a Likelihood fit which is performed on the data sample to determin...

This article approaches the problem of selecting significant principal components from a Bayesian model selection perspective. The resulting Bayes rule provides a simple graphical technique that can be used instead of (or together with) the popular scree plot to determine the number of significant components to retain. We study the theoretical properties of the new method and show, by examples ...