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 plots with 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 tutorial are available on the ggeasy official github repository. If you are instead (or maybe, at the same) 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

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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Recent papers

  • Pasquale Dolce, Cristina Davino, Domenico Vistocco (2021) Quantile composite-based path modeling: algorithms, properties and applications. Advances in Data Analysis and Classification. Abstract  RG DOI  pdf
  • Rosa Fabbricatore, Maria Iannario, Rosaria Romano, Domenico Vistocco (2021) Component-based structural equation modeling for the assessment of psycho-social aspects and performance of athletes. AStA Advances in Statistical Analysis. Abstract  RG DOI  pdf
  • Cristina Davino, Marco Gherghi, Silvia Sorana, Domenico Vistocco (2021) Measuring Social Vulnerability in an Urban Space Through Multivariate Methods and Models. Social Indicator Research, 157, 1179-1201. Abstract  RG DOI  pdf
  • Sara Spognardi, Domenico Vistocco, Lucio Cappelli, Patrizia Papetti (2021) Impact of organic and “protected designation of origin” labels in the perception of olive oil sensory quality. British Food Journal, 123, 8, 2641-2669. Abstract  RG DOI
  • Cristina Davino, Pasquale Dolce, Stefania Taralli, Domenico Vistocco (2020) Composite-Based Path Modeling for Conditional Quantiles Prediction. An Application to Assess Health Differences at Local Level in a Well-Being Perspective. Social Indicator Research. Abstract  RG DOI  pdf

Recent seminars, short courses and conference reports

  • Short course: The R tidyverse. (30 November 2021) More info...
  • Ansia da valutazione, procrastinazione, grinta e autoefficacia: quale rapporto?. (23 October 2021) More info...
  • La certezza assoluta ed altre finzioni. Leggerezza, inganni ed estetica del caso (Italian). (9 September 2021) More info...
  • Effects of distance teaching on students and their families: the experience at Federico II University of Naples. (6 September 2021) More info...
  • Exploring the Effects of E-learning on Students and Families: the Case of the University of Naples. (11 July 2021) YouTube More info...