1. Basic age-modelling Find ages for dated and undated depths E.g., linear interpolation, regression, spline (gaps) Choose which one looks nicest... How treat point estimates? (mid/max, multimodal)‏

2. Bayesian age-modelling Bayesian = combine data with other info  14 C dates and depth info  stratigraphical ordering / position e.g., wiggle-match dating  Constraints on e.g. likely accumulation rates  Other dates, e.g. pollen events, 210 Pb (…)  Outlier analysis Usually done by millions of simulations

3. Wiggle-match dating

4. Outlier analysis Reasons: site, error, lab? Give prior outlier probabilities to dates Iteration i: is date within 2 lengths sd? If not, label date and shift to fit [Labelled / total]  posterior outlier prob. No need to remove outliers! Fit F: 1 – mean(posterior outlier prob.)‏

5. OxCal Extract OxCal directory to C:\Program Files Open.../OxCal/Index.html in Firefox R_Date( “test”, 2450, 50); Save file, run Run examples from manual

6. Bpeat Extract Bpeat.zip somewhere Open R there (or change dir) source(“Bpeat.R”) SetCore(“MSB2K”,2) TestRun() FinalRun( 0.1 ) # just a short run... DepthChron()

7. The future of Bpeat: Bacon

8. Bacon Muscles and fat – robust, yet flexible Floppy/crusty – flexibility can be adapted Can be cut to your liking – hiatuses Cured – Bpeat bugs repaired MacBacon – multi-platform Pigs are smart – combine prior info + new data Pigs can fly – workshop in Mexico

9. Age-modelling … your own data? Try the different software pieces What are best settings for your site? Do you agree with the age estimates? Differences between approaches