The tesselle packages can be used to explore and analyze common data types in archaeology: count data, compositional data and chronological data.

Most of our packages are distributed on CRAN, development versions and non-CRAN packages (e.g. WIP packages and large data packages) can be installed from our repository.

Install the complete suite with:


Browse the documentation on

Count data


An easy way to examine archaeological count data. tabula provides a convenient and reproducible toolkit for relative dating by matrix seriation (reciprocal ranking, CA-based seriation). The package provides several tests and measures of diversity: heterogeneity and evenness (Brillouin, Shannon, Simpson, etc.), richness and rarefaction (Chao1, Chao2, ACE, ICE, etc.), turnover and similarity (Brainerd-Robinson, etc.). The package make it easy to visualize count data and statistical thresholds: rank vs. abundance plots, heatmaps, Ford (1962) and Bertin (1977) diagrams. Read the doc…

Compositional data


Sourcing archaeological materials by chemical composition. nexus allows the exploration and analysis of compositional data in the framework of Aitchison (1986). It provides tools for chemical fingerprinting and source tracking of ancient materials. Initial development is in progress. Read the doc…

Chronological data


A toolkit for absolute dating and analysis of chronological patterns. This package includes functions for chronological modeling and dating of archaeological assemblages from count data. It allows to compute time point estimates and density estimates of the occupation and duration of an archaeological site. Read the doc…


Statistical analysis of archaeological dates and groups of dates. This package allows to post-process Markov Chain Monte Carlo (MCMC) simulations from ChronoModel, Oxcal or BCal. This package provides functions for the study of rhythms of the long term from the posterior distribution of a series of dates (tempo and activity plot). It also allows the estimation and visualization of time ranges from the posterior distribution of groups of dates (e.g. duration, transition and hiatus between successive phases). Read the doc…

Multivariate data analysis


Simple Principal Components Analysis (PCA) and Correspondence Analysis (CA) based on the Singular Value Decomposition (SVD). This package provides S4 classes and methods to compute, extract, summarize and visualize results of multivariate data analysis. It also includes methods for partial bootstrap validation described in Greenacre (1984) and Lebart, Piron, and Morineau (2006). Read the doc…

Data visualization


Colour schemes ready for each type of data (qualitative, diverging or sequential), with colours that are distinct for all people, including colour-blind readers. This package provides an implementation of Paul Tol (2018) and Fabio Crameri (2018) colour schemes for use with graphics or ggplot2. It provides tools to simulate colour-blindness and to test how well the colours of any palette are identifiable. Several scientific thematic schemes (geologic timescale, land cover, FAO soils, etc.) are also implemented. Read the doc…



Datasets for teaching quantitative approaches and modeling in archaeology and paleontology. folio provides several types of data related to broad topics (cultural evolution, radiocarbon dating, paleoenvironments, etc.), which can be used to illustrate statistical methods in the classroom (multivariate data analysis, compositional data analysis, diversity measurement, etc.). Read the doc…


Datasets for chronological modelling. This package provides models and data to reproduce results from chronos examples and vignettes. Read the doc…



A collection of classes that represent archaeological data. This package provides a set of S4 classes that represent different special types of matrix (absolute/relative frequency, presence/absence data, co-occurrence matrix, etc.) upon which package developers can build subclasses. It also provides a set of generic methods (mutators and coercion mechanisms) and functions (e.g. predicates). In addition, a few classes of general interest (e.g. that represent stratigraphic relationships) are implemented. Read the doc…

Aitchison, John. 1986. The Statistical Analysis of Compositional Data. Monographs on Statistics and Applied Probability. London: Chapman and Hall.

Bertin, Jacques. 1977. La graphique et le traitement graphique de l’information. Nouvelle bibliothèque scientifique. Paris: Flammarion.

Ford, James A. 1962. A Quantitative Method for Deriving Cultural Chronology. Technical Manual 1. Washington, DC: Pan American Union.

Greenacre, Michael J. 1984. Theory and Applications of Correspondence Analysis. London: Academic Press.

Lebart, Ludovic, Marie Piron, and Alain Morineau. 2006. Statistique exploratoire multidimensionnelle : Visualisations et inférences en fouilles de données. Paris: Dunod.



If you see mistakes or want to suggest changes, please create an issue on the source repository.


Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".