The Strucplot Framework: Visualizing Multi-way Contingency Tables with vcd

By David Meyer, Achim Zeileis, Kurt Hornik. 2006

388 citations recorded by the source corpus.

This paper describes the `strucplot' framework for the visualization of multi-way contingency tables. Strucplot displays include hierarchical conditional plots such as mosaic, association, and sieve plots, and can be combined into more complex, specialized plots for visualizing conditional independence, GLMs, and the results of independence tests. The framework's modular design allows flexible customization of the plots' graphical appearance, including shading, labeling, spacing, and legend, by means of graphical appearance control (`grapcon') functions. The framework is provided by the R package vcd. (author's abstract)

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Food Science

View Paper: https://www.semanticscholar.org/paper/24162c1a46669f94356854176ece8548bf7fb989

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Computer Vision and Pattern Recognition

In Food Science

Citations in the corpus

Implementing a Class of Permutation Tests: The coin Package (2008, methodology): “Single-step adjusted p -values for each cell of the contingency table corresponding to this maximum test can be computed via was used for the computations, Figure 1 was created using the vcd package (Meyer, Zeileis, and Hornik 2006).”
The VGAM Package for Categorical Data Analysis (2010, methodology): “A package for visualizing categorical data in R is vcd (Meyer et al. 2006, 2009).”
How Sensitive Are Ecosystem Services in European Forest Landscapes to Silvicultural Treatment (2015, methodology): “As the backbone of our descriptive analysis we chose mosaic plots [30] as implemented in the R-package vcd [31].”