bpca

bpca is an R package for biplot analysis based on principal components.

Key Features

• PCA-based Biplot analysis in reduced-dimensional spaces (2D and 3D).
• Multiple factorization methods (hj, sqrt, jk, gh) for different interpretations.
• Quality diagnostics for dimensionality reduction and representation fidelity.
• Reporting support with xtable(bpca(...)) and print(..., type = "html").

Installation

Install from CRAN:

install.packages("bpca")

Install the development version from GitHub:

# install.packages("remotes")
remotes::install_github("jcfaria/bpca")

Quick Start

library(bpca)

# Example with the classic iris dataset
bp <- bpca(iris[-5], d = 1:2)
plot(
  bp,
  var.col = "blue",
  var.factor = 2,
  main = "Biplot - Iris Dataset"
)

For more complete examples, see:

• demo("bpca", package = "bpca")
• vignette("bpca-overview", package = "bpca")

Project Layout

• /R: Core computational and plotting functions.
• /data: Example datasets shipped with the package.
• /demo: Runnable demos illustrating usage.
• /man: Documentation (.Rd files).
• /inst: Extra package materials (e.g. citations).
• /vignettes: Vignettes and tutorials.

Contributing

Contributions are welcome. Open an Issue or submit a Pull Request on github.com/jcfaria/bpca with:

• Bug fixes and performance improvements.
• Documentation and usability improvements.
• New ideas for diagnostics and visualization workflows.

Roadmap

• Expand test coverage for edge cases and plotting behavior.
• Add practical vignettes with real-world datasets.
• Improve CI signals and package quality checks.

Developed by:
Faria, J. C.; Allaman, I. B.
Universidade Estadual de Santa Cruz - UESC
Departamento de Ciências Exatas - DCEX
Ilhéus - Bahia - Brasil

Demétrio, C. G. B.
Universidade de São Paulo - USP
Escola Superior de Agricultura Luiz de Queiroz - ESALQ
Piracicaba - São Paulo - Brasil