Bayesian Chronological Data Interpretation: Where Now?

  • Caitlin E. Buck
Chapter
Part of the Lecture Notes in Statistics book series (LNS, volume 177)

Summary

This chapter summarizes the current state of the art in the use of Bayesian statistical models originally devised for chronology building in archaeology. Over the last 10 years, archaeologists have begun routinely to adopt such methods based on these models because they offer a formal, coherent framework for the integration of chronometric (typically radiocarbon) data and other sources of absolute and relative chronological information. Since they allow us to combine both relative and absolute dating evidence from different sources, such methods typically lead to less uncertainty in the final date estimates than other methods which focus on one piece of evidence at a time. Until recently, such methods have only routinely been used by archaeologists, but many of them clearly have potential for chronology building in other disciplines too. Counterpoint to this chapter is given by the discussions of the practical, routine application of its methods by Bayliss and Bronk Ramsey (Chapter 2). In addition, further development s to some of the ideas here are discussed by Lanos (Chapter 3) with respect to archaeomagnetism, Sahu (Chapter 5) with respect to model choice and Millard (Chapter 11) with respect to techniques other than radiocarbon.

Keywords

Markov Chain Monte Carlo Prior Information Calibration Data Posteriori Probability Before Present 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© Springer-Verlag London 2004

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  • Caitlin E. Buck

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