Grouped Hyper Data Frame

Author

Tingting Zhan

Published

December 5, 2025

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, with limited support from National Institutes of Health, U.S. Department of Health and Human Services grants

R01CA222847 (I. Chervoneva, T. Zhan, and H. Rui)
R01CA253977 (H. Rui and I. Chervoneva).

The author thanks

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

The author present a collections of packages (these packages)

groupedHyperframe (CRAN, Github, v0.3.2.20251203)
groupedHyperframe.random (CRAN, Github, v0.2.0.20251031)
hyper.gam (CRAN, Github, v0.2.1.20151031) and
maxEff (CRAN, Github, v0.2.1)

BibTeX and/or BibLaTeX entries for LaTeX users

@Manual{,
  title = {groupedHyperframe: Grouped Hyper Data Frame: An Extension of
Hyper Data Frame},
  author = {Tingting Zhan},
  note = {R package version 0.3.2.20251203},
  url = {https://github.com/tingtingzhan/groupedHyperframe},
}

@Manual{,
  title = {groupedHyperframe.random: Simulated Grouped Hyper Data Frame},
  author = {Tingting Zhan},
  note = {R package version 0.2.0.20251031},
  url = {https://tingtingzhan.quarto.pub/groupedhyperframe/random},
}

@Manual{,
  title = {hyper.gam: Generalized Additive Models with Hyper Column},
  author = {Tingting Zhan and Inna Chervoneva},
  year = {2025},
  note = {R package version 0.2.0},
  url = {https://CRAN.R-project.org/package=hyper.gam},
  doi = {10.32614/CRAN.package.hyper.gam},
}

@Manual{,
  title = {maxEff: Additional Predictor with Maximum Effect Size},
  author = {Tingting Zhan and Inna Chervoneva},
  note = {R package version 0.2.1},
  url = {https://github.com/tingtingzhan/maxEff},
}

This Quarto book documents

the creation of grouped hyper data frame (2 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 Introduction, 2 Grouped Hyper Data Frame, 3 Grouping ppp-Hypercolumn, 4 Simulation, 5 Quantile Index and 6 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.