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Prehistoric Demography

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Tika pop

In collaboration with former PhD-student Mike Price and an interdisciplinary team of scholars, I have recently become interested in problems of reconstruction of past populations.  A central feature of this work is improving inference for past populations. We can do this by applying modern Bayesian statistical methods to historical inference, but also by building in theory from age-structured demography. Current work with Mike,  Julie HoggarthClaire Ebert, and Kyle Bocinsky has focused on inference about population history of the Maya Lowlands.

We anticipate that this project will have substantial synergies with our work on adaptation, human life-history evolution, and evolutionary economics.

We already have a package for Bayesian inference for collections of radiocarbon samples available on GitHub. This package uses some routines in another package, yada (yet another demographic analysis package).

Representative Papers

Price, M.H., J.M. Capriles, J. Hoggarth, R.K. Bocinsky, C.E. Ebert, and J.H. Jones. (2021). End-to-end Bayesian analysis for summarizing sets of radiocarbon dates. 135: 105473. Journal of Archaeological Science. (doi: 10.1016/j.jas.2021.105473)

Price, M.H., J.M. Capriles, J. Hoggarth, R.K. Bocinsky, C.E. Ebert, and J.H. Jones. (2020) End-to-end Bayesian analysis of 14C dates reveals new insights into lowland Maya demography. (bioRXiv: 10.1101/2020.07.02.185256)