DV blog

Thoughts on statistics, R, research, and other distractions.

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Marginal plots with ggside

A marginal plot is a combination of a bivariate plot (typically a scatter plot) and one/two univariate plots (density, boxplot, dotplot, …). It is an interesting plot since you can inspect both the relationship between two variables and the distribution of each variable. Even if there are several options to obtain a marginal plot, here I exploit ggside, an useful extension for ggplot2. Note: ggside can be used also for adding univariate plot(s) to a generic ggplot.

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Easy customisation of ggplot2: ggeasy

If you are interested to customise a ggplot2 graph without going crazy in remembering all the technicalities for rotating labels, removing or rotaging axes, removing or changing appeareance of legends, change the text appearance, I suggest to inspect ggeasy. Documentation and tutorials are available on the ggeasy official github repository. Instead (or maybe, at the same), if you are instead interested to master ggplot2 without shortcuts, please refer to the must-read book ggplot2: Elegant Graphic for Data Analysis, freely available online.

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DESPOTA (DEndogram Slicing through a PermutatiOn Test Approach) is a novel approach exploiting permutation tests in order to automatically detect a partition among those embedded in a dendrogram. Unlike the traditional approach, DESPOTA includes in the search space also partitions not corresponding to horizontal cuts of the dendrogram. The output of hierarchical clustering methods is typically displayed as a dendrogram describing a family of nested partitions. However, the exploitable partitions are usually restricted to those relying on horizontal cuts of the tree, missing the possibility to explore the whole set of partitions housed in the dendrogram.

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About DV blog

I decided to collect material related to my experience on R, statistics, coding and other things of my interest on the DV blog. Since I learned (and continue to learn) a lot from the web, I hope that this material will be useful and of interest to those who have interests in common with me. Since it is not a book, the published material does not follow any order but is meant to be browsed/searched by date or by topic, rather than according to a particular sequence.

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This is not a help service for all your R and statistical questions, so please try to avoid to post general questions in the comments, or send them to me by email. Please, limit to comments related to the published content. If you have questions about data analysis, ask for help on crossvalidated.com. If you have questions about R, ask for help on stackoverflow.com. Please, be polite in your comment: you do not necessarily have to agree with my posts but you can always kindly manifest your opinion.

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