Grouped Hyper Data Frame

Author

Tingting Zhan

Published

February 3, 2026

Preface

Mirrors of this Quarto book can be accessed at the following URLs. These free hosting services may experience occasional downtime.

https://tingtingzhan.quarto.pub/groupedhyperframe/

https://tingtingzhan-groupedhyperframe.netlify.app

This is an entertaining-but-useless project carried out primarily during Tingting Zhan’s leisure hours. The author thanks

  • Erjia Cui’s contribution to function hyper.gam::hyper_gam().

The author present a collections of packages (these packages)

BibTeX and/or BibLaTeX entries for LaTeX users 
@Manual{,
  title = {groupedHyperframe: Grouped Hyper Data Frame},
  author = {Tingting Zhan},
  year = {2026},
  note = {R package version 0.3.4, commit fb36e9f49c5106b5752cf5f58a8faaa172760f47},
  url = {https://github.com/tingtingzhan/groupedHyperframe},
}

@Manual{,
  title = {groupedHyperframe.random: Simulated Grouped Hyper Data Frame},
  author = {Tingting Zhan},
  year = {2026},
  note = {R package version 0.2.2, commit e41c7fa55d2c0c4b5a5c352a57b72265daee90b0},
  url = {https://github.com/tingtingzhan/groupedHyperframe.random},
}

@Manual{,
  title = {hyper.gam: Generalized Additive Models with Hyper Column},
  author = {Tingting Zhan},
  year = {2026},
  note = {R package version 0.2.2, commit 3e3d6f8157e787860f538f81acb09bac7c96f62f},
  url = {https://github.com/tingtingzhan/hyper.gam},
}

@Manual{,
  title = {maxEff: Additional Predictor with Maximum Effect Size},
  author = {Tingting Zhan},
  year = {2026},
  note = {R package version 0.2.2, commit 1ed1eb090deca98ea4339cc1ec87621284105b79},
  url = {https://github.com/tingtingzhan/maxEff},
}

These packages require R version 4.5.0 (released 2025-04-11) or higher (macOS, Windows, Linux). Readers are encouraged to learn more about the full details of these packages in 6  About.

Listing 1 installs these packages from CRAN,

Listing 1: Install these packages from CRAN 
utils::install.packages('groupedHyperframe')
utils::install.packages('groupedHyperframe.random')
utils::install.packages('hyper.gam')
utils::install.packages('maxEff')

This Quarto book documents

  • the creation of grouped hyper data frame (1  Grouped Hyper Data Frame);
  • the creation of a grouped hyper data frame with one-and-only-one point-pattern hypercolumn (Creation);
  • the batch process on eligible marks (Batch Process on Eligible Marks) for the one-and-only-one point-pattern hypercolumn in a (grouped) hyper data frame;
  • the computation of various summary statistics (Summarization) from one or more function-value-table hypercolumn(s) of a (grouped) hyper data frame;
  • the aggregation (Aggregation) of summary statistics, over a (nested) grouping structure, in a grouped hyper data frame.
  • the simulation of superimposed (marked) point-patterns via vectorized parameterization (Simulated Point-Pattern);
  • the simulation of grouped hyper data frame via matrix parameterization (Simulated Grouped Hyper Data Frame).

The Chapters 1  Grouped Hyper Data Frame, 2  Grouping ppp-Hypercolumn, 3  Simulation, 4  Quantile Index and 5  Predictor with Maximum Effect Size of this book explain how to use this package to a general audience.

Rest of this book explain why and how these packages works for readers with advanced expertise in the R programming language.