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Description

Ancient Demographic Modelling Using Radiocarbon.

Provides tools to directly model underlying population dynamics using date datasets (radiocarbon and other) with a Continuous Piecewise Linear (CPL) model framework. Various other model types included. Taphonomic loss included optionally as a power function. Model comparison framework using BIC. Package also calibrates 14C samples, generates Summed Probability Distributions (SPD), and performs SPD simulation analysis to generate a Goodness-of-fit test for the best selected model. Details about the method can be found in Timpson A., Barberena R., Thomas M. G., Mendez C., Manning K. (2020) <doi:10.1098/rstb.2019.0723>.

UCL Research Software Development UCL Research Software Development Max Planck Institute for the Science of Human History Pan African Evolution ResearchGroup

Build Status

ADMUR

Ancient Demographic Modelling Using Radiocarbon

Tools to directly model underlying population dynamics using chronological datasets (radiocarbon and other) with a variety of models, including Continuous Piecewise Linear (CPL) model framework. Optional taphonomy. Model comparison framework using BIC. Package also calibrates 14C samples, and generates Summed Probability Distributions (SPD). CPL modelling directly estimates the most likely population trajectory given a dataset, using SPD simulation analysis to generate a Goodness-of-fit test for the best selected model.

Please contact [email protected] in the first instance to make suggestions, report bugs or request help.

Installation

Install from CRAN, then load

install.packages('ADMUR')
library('ADMUR')

Guide

Refer to the vignette 'guide' for detailed support and examples.

vignette('guide', package = 'ADMUR')

References

This package accompanies the following paper:

Timpson A., Barberena R., Thomas M. G., Mendez C., Manning K. 2020. "Directly modelling population dynamics in the South American Arid Diagonal using 14C dates",Philosophical Transactions B. https://doi.org/10.1098/rstb.2019.0723.

Citations available as follows:

citation(package='ADMUR')

ADMUR was written in collaboration with:

  • University College London
    • Department of Genetics, Evolution and Environment
    • Molecular and Cultural Evolution Laboratory
    • UCL Research Software Development
  • Max Planck Institute for the Science of Human History
    • Department of Archaeology
    • Pan African Evolution ResearchGroup

Special thanks to Yoan Diekmann for his influential inferential input.

Also thanks to the following who have reported bugs, requested additional functionality, offered constructive criticism, or provided other advice:

  • Gregor Seyer
  • Uwe Ligges
  • Prof Brian Ripley
  • Enrico Crema
  • Ricardo Fernandes.

Metadata

Version

1.0.3

License

Unknown

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