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:globe_with_meridians: Sourcing Archaeological Materials by Chemical Composition

Home Page: https://packages.tesselle.org/nexus/

License: GNU General Public License v3.0

R 89.45% TeX 10.55%

archaeological-science archaeology archaeometry compositional-data provenance-studies r-package

nexus's Introduction

tesselle

Overview

The tesselle suite is a collection of packages for research and teaching in archaeology. These packages focus on quantitative analysis methods developed for archaeology. The tesselle packages are designed to work seamlessly together and to complement general-purpose and other specialized statistical packages. These packages can be used to explore and analyze common data types in archaeology: count data, compositional data and chronological data.

The tesselle package is designed to make it easy to install and load key packages from the tesselle suite in a single step.

To cite tesselle in publications use:

  Frerebeau N (2024). _tesselle: Easily Install and Load 'tesselle'
  Packages_. Université Bordeaux Montaigne, Pessac, France.
  doi:10.5281/zenodo.6500491 <https://doi.org/10.5281/zenodo.6500491>,
  R package version 1.5.0, <https://packages.tesselle.org/tesselle/>.

This package is a part of the tesselle project
<https://www.tesselle.org>.

Installation

You can install the released version of tesselle from CRAN with:

install.packages("tesselle")

And the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("tesselle/tesselle")

Usage

library(tesselle) will load the core packages:

tabula: analysis and visualization of archaeological count data;
kairos: analysis of chronological patterns from archaeological count data;
nexus: analysis of compositional data;

And two companion packages:

dimensio: multivariate analysis;
isopleuros: ternary plots.

library(tesselle)
#> --- Attaching packages -------------------------------------- tesselle 1.5.0 ---
#> * dimensio    0.6.0
#> * isopleuros  1.2.0
#> * kairos      2.1.0
#> * nexus       0.2.0
#> * tabula      3.0.1

Contributing

Please note that the tesselle project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

nexus's People

Contributors

Stargazers

Watchers

nexus's Issues

Add "mixed-mode" analysis

References:

Baxter et al. (2008). ON STATISTICAL APPROACHES TO THE STUDY OF CERAMIC ARTEFACTS USING GEOCHEMICAL AND PETROGRAPHIC DATA. Archaeometry, 50(1): 142-157. DOI: https://doi.org/10.1111/j.1475-4754.2007.00359.x.

Missing values policy

Define how missing values are handled:

Values below detection limit
Amount not observed or missing
Amount is absolutely zero

References:

Boogaart, K. G. v. d., Tolosana-Delgado, R., Bren, M. (2006). Concepts for handling of zeros and missing values in compositional data. In Pirard, E. (ed.), Proccedings of the IAMG'2006 Annual Conference on Quantitative Geology from multiple sources, (September 2006; Liege, Belgium), URL: http://stat.boogaart.de/Publications/iamg06_s07_01.pdf.

Use ILR instead of CLR transformation for PCA

Aitchison, J. and Greenacre, M. (2002), Biplots of compositional data. Journal of the Royal Statistical Society: Series C (Applied Statistics), 51: 375-392. https://doi.org/10.1111/1467-9876.00275

Filzmoser, P., Hron, K. and Reimann, C. (2009), Principal component analysis for compositional data with outliers. Environmetrics, 20: 621-632. https://doi.org/10.1002/env.966

Add modified Mahalanobis filters

References:

Beier, T., Mommsen, H. (1994). Modified Mahalanobis filters for grouping pottery by chemical composition. Archaeometry, 36(2):287-306. DOI: https://doi.org/10.1111/j.1475-4754.1994.tb00971.x.
Mommsen, H. (2012). The importance of a reliable grouping - neutron activation analysis (NAA) data of Mycenaean pottery sherds re-evaluated with the Bonn filter method. Journal of Archaeological Science, 39:704-707. DOI: https://doi.org/10.1016/j.jas.2011.11.002.
Mommsen, H., Kreuser, A., Weber, J. (1988). A method for grouping pottery by chemical composition. Archaeometry, 30(1):47-57. DOI: https://doi.org/10.1111/j.1475-4754.1988.tb00434.x.
Riehle K, Kistler E, Öhlinger B, Heitz C, Ben-Shlomo D, Jung R, Mommsen H, Sterba JH, Gimatzidis S, Fantalkin A, Prillwitz S, Hein A, Geissler L, Lehmann G, Kindberg Jacobsen J, Posamentir R, Schlotzhauer U. (2023). Neutron activation analysis in Mediterranean Archaeology: current applications and future perspectives. Archaeological and Anthropological Science, 15(3):25. DOI: https://doi.org/10.1007/s12520-023-01728-1.
Sterba, J. H., Mommsen, H., Steinhauser, G., Bichler, M. (2009). The influence of different tempers on the composition of pottery. Journal of Archaeological Science, 36:1582-1589. DOI: https://doi.org/10.1016/j.jas.2009.03.022

Missing values imputation

#3
Multiplicative replacement of zeros
Multiplicative replacement of missing values

References:

Hron, K., Templ, M., Filzmoser, P. (2010). Imputation of missing values for compositional data using classical and robust methods, Computational Statistics & Data Analysis, 54(12): 3095-3107. DOI : https://doi.org/10.1016/j.csda.2009.11.023
Martin-Fernandez, J. A., Barcelo-Vidal, C., Pawlowsky-Glahn, V. (2003). Dealing With Zeros and Missing Values in Compositional Data Sets Using Nonparametric Imputation. Mathematical Geology, 35(3): 253-278. DOI: https://doi.org/10.1023/A:1023866030544

tesselle / nexus Goto Github PK

nexus's Introduction

tesselle

Overview

Installation

Usage

Contributing

nexus's People

Contributors

Stargazers

Watchers

nexus's Issues

Add "mixed-mode" analysis

Missing values policy

Use ILR instead of CLR transformation for PCA

Add modified Mahalanobis filters

Missing values imputation

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