Bayesian interpretation of radiocarbon results
Over the last thirty years radiocarbon dating has been widely used in archaeology and related fields to address a wide-range of chronological questions. Because of some inherent stochastic factors of a complex nature, radiocarbon dating presents a rich source of challenging statistical problems. The chronological questions posed commonly involve the interpretation of groups of radiocarbon determinations and often substantial amounts of a priori information are available. The statistical techniques used up to very recently could only deal with the analysis of one determination at a time, and no prior information could be included in the analysis. However, over the last few years some problems have been successfully tackled using the Bayesian paradigm. In this thesis we expand that work and develop a general statistical framework for the Bayesian interpretation of radiocarbon determinations. Firstly we consider the problem of radiocarbon calibration and develop a novel approach. Secondly we develop a statistical framework which permits the inclusion of prior archaeological knowledge and illustrate its use with a wide range of examples. We discuss various generic problems some of which are, replications, summarisation,
Christen, JosĂ© AndrĂ©s
QA276 Mathematical statistics
Bayesian interpretation of radiocarbon results. Over the last thirty years radiocarbon dating has been widely used in archaeology and related fields to address a wide-range of chronological questions. Because of some inherent stochastic factors of a complex nature, radiocarbon dating presents a rich source of challenging statistical problems. The chronological questions posed commonly involve the interpretation of groups of radiocarbon determinations and often substantial amounts of a priori information are available. The statistical techniques used up to very recently could only deal with the analysis of one determination at a time, and no prior information could be included in the analysis. However, over the last few years some problems have been successfully tackled using the Bayesian paradigm. In this thesis we expand that work and develop a general statistical framework for the Bayesian interpretation of radiocarbon determinations. Firstly we consider the problem of radiocarbon calibration and develop a novel approach. Secondly we develop a statistical framework which permits the inclusion of prior archaeological knowledge and illustrate its use with a wide range of examples. We discuss various generic problems some of which are, replications, summarisation,
bayesian interpretation radiocarbon result radiocarbon_date widely_use archaeology relate field address wide_range chronological question inherent stochastic factor complex nature radiocarbon_date present rich_source challenge statistical problem chronological question_pose commonly involve interpretation group radiocarbon_determination often substantial amount priori information_available statistical_technique use recently could deal analysis determination time prior information could include analysis however problem successfully tackle use bayesian paradigm expand work develop general statistical framework bayesian interpretation radiocarbon_determination firstly consider problem radiocarbon calibration develop_novel approach secondly develop statistical framework permit inclusion prior archaeological_knowledge illustrate use wide_range example discuss_various generic problem replication