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Using car4ams, the Bayesian AMS Data Analysis Code

Published online by Cambridge University Press:  18 July 2016

V Palonen ,
P Tikkanen  and
J Keinonen
V Palonen*
Affiliation:
P.O. Box 43, Department of Physics, 00014 University of Helsinki, Finland
P Tikkanen
Affiliation:
P.O. Box 43, Department of Physics, 00014 University of Helsinki, Finland
J Keinonen
Affiliation:
P.O. Box 43, Department of Physics, 00014 University of Helsinki, Finland
*
Corresponding author. Email: vesa.palonen@helsinki.fi.
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Abstract

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The Bayesian CAR (continuous autoregressive) model for accelerator mass spectrometry (AMS) data analysis delivers uncertainties with less scatter and bias. Better detection and estimation of the instrumental error of the AMS machine are also achieved. Presently, the main disadvantage is the several-hour duration of the analysis. The Markov chain Monte Carlo (MCMC) program for CAR model analysis, car4ams, has been made freely available under the GPL license. Included in the package is an R program that analyzes the car4ams output and summarizes the results in graphical and spreadsheet formats. We describe the main properties of the CAR analysis and the use of the 2 parts of the program package for radiocarbon AMS data analysis.

Information

Type
Calibration, Data Analysis, and Statistical Methods
Information
Radiocarbon , Volume 52 , Issue 3: 20th Int. Radiocarbon Conference Proceedings , 2010 , pp. 948 - 952
Copyright
Copyright © 2010 by the Arizona Board of Regents on behalf of the University of Arizona 

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