Correspondence Analysis in R, with Two- and Three-dimensional Graphics: The ca Package

By Oleg Nenadić, Michael J. Greenacre. 2007

683 citations recorded by the source corpus.

We describe an implementation of simple, multiple and joint correspondence analysis in R. The resulting package comprises two parts, one for simple correspondence analysis and one for multiple and joint correspondence analysis. Within each part, functions for computation, summaries and visualization in two and three dimensions are provided, including options to display supplementary points and perform subset analyses. Special emphasis has been put on the visualization functions that offer features such as different scaling options for biplots and three-dimensional maps using the rgl package. Graphical options include shading and sizing plot symbols for the points according to their contributions to the map and masses respectively.

Subfields: Food Science

View Paper: https://www.semanticscholar.org/paper/65bb38c575760dccb8e0a4a9394e1b40ef4d5592

How researchers see this paper

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

In Food Science

Citations in the corpus

Emotion shapes the diffusion of moralized content in social networks (2017, methodology): “S1 to S3 Tables S1 to S19 References (1-21)”
Tweeting From Left to Right (2015, methodology): “Instead, we use correspondence analysis (Greenacre, 1984, 2010), adapting its implementation in the ca package for R (Nenadic and Greenacre, 2007).”
Exploratory Multivariate Analysis by Example Using R (2010, methodology): “It is similar to the R function ca from package ca (Nenadi´c and Greenacre 2007), though its graphics are a bit more user-friendly.”
Predicting impacts of climate change on biodiversity: a role for semi‐mechanistic community‐level modelling (2011, methodology): “We used this information to ordinate the approaches using multiple correspondence analysis (Nenadic & Greenacre, 2007).”
missMDA: A Package for Handling Missing Values in Multivariate Data Analysis (2016, methodology): “Their strategy is implemented in the R package ca (Nenadic and Greenacre 2007) using the function mjca with argument subsetcol.”
Current threats faced by Neotropical parrot populations (2017, methodology): “To study the pattern of association among reported threats and population trends, a multiple correspondence analysis (MCA) was carried out using the ca package in the R statistical environment (Nenadic and Greenacre, 2007, R Development Core Team, 2016).”