Using car4ams, the Bayesian AMS Data Analysis Code
Bibliographic Data
| ID | 9245267 |
|---|---|
| Authors | Vesa Palonen (0000-0001-9589-7989), P Tikkanen, J Keinonen |
| Year | 2010 |
| Volume | 52 |
| Issue | 3 |
| Pages | 948-952 |
| Publication date | 2010-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Radiocarbon (JOURNAL) |
| Journal identifiers | ISSN: 0033-8222 • E-ISSN: 1945-5755 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s0033822200046051 |
| OpenAlex | W2217251178 |
| Language | EN |
| Citations received | 1 |
| References cited | 5 |
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
Accelerator mass spectrometry · Autoregressive model · Bayesian probability · Data mining · Markov chain Monte Carlo · Monte Carlo method · Radiocarbon dating · Statistics · Archaeology and ancient environmental studies · Computer Science · Isotope Analysis in Ecology · Mathematics · Metabolomics and Mass Spectrometry Studies · Artificial Intelligence
| Citations per year | 0.11 |
|---|---|
| Citation span | 2017 - 2017 (1) |
| Highly cited | No |