Grouped Hyper Data Frame

Author

Tingting Zhan

Published

February 9, 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 1f73749ec35a679ba2cb6c79ca7f72cae2dda544},
  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 ca2416a222ed816a0b5793767fd7e1d846a84ee5},
  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 312d2e2414d2166a6c8578f6e145bff38c32b5d8},
  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 da0ff87783c800587a3886d04dbffac21e253420},
  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.