- output_data
The return value from the updating function
PPcalibrate. Optionally, the output data can have an extra list item
named label which is used to set the label on the plot legend.
- n_realisations
Number of randomly sampled realisations to be drawn from MCMC posterior
and plotted. Default is 10.
- plot_realisations_colour
The colours to be used to plot the individual realisations.
Default is greyscale (otherwise should have same length as number of realisations).
- realisations
Specific indices of realisations (in thinned version) to plot if user does not
want to sample realisations randomly). If specified will override n_realisations.
- calibration_curve
This is usually not required since the name of the
calibration curve variable is saved in the output data. However, if the
variable with this name is no longer in your environment then you should pass
the calibration curve here. If provided, this should be a dataframe which
should contain at least 3 columns entitled calendar_age, c14_age and c14_sig.
This format matches intcal20.
- plot_14C_age
Whether to use the radiocarbon age (\({}^{14}\)C yr BP) as
the units of the y-axis in the plot. Defaults to TRUE. If FALSE uses
F\({}^{14}\)C concentration instead.
- plot_cal_age_scale
(Optional) The calendar scale to use for the x-axis. Allowed values are
"BP", "AD" and "BC". The default is "BP" corresponding to plotting in cal yr BP.
- interval_width
The confidence intervals to show for the
calibration curve. Choose from one of "1sigma" (68.3%),
"2sigma" (95.4%) and "bespoke". Default is "2sigma".
- bespoke_probability
The probability to use for the confidence interval
if "bespoke" is chosen above. E.g., if 0.95 is chosen, then the 95% confidence
interval is calculated. Ignored if "bespoke" is not chosen.
- denscale
(Optional) Whether to scale the vertical range of the Poisson process mean rate plot
relative to the calibration curve plot. Default is 3 which means
that the maximum of the mean rate will be at 1/3 of the height of the plot.
- resolution
The distance between calendar ages at which to calculate the value of the rate
\(\lambda(t)\). These ages will be created on a regular grid that automatically covers
the calendar period specified in output_data. Default is 1.
- n_burn
The number of MCMC iterations that should be discarded as burn-in (i.e.,
considered to be occurring before the MCMC has converged). This relates to the number
of iterations (n_iter) when running the original update functions (not the thinned output_data).
Any MCMC iterations before this are not used in the calculations. If not given, the first half of the
MCMC chain is discarded. Note: The maximum value that the function
will allow is n_iter - 100 * n_thin (where n_iter and n_thin are the arguments that were given to
PPcalibrate) which would leave only 100 of the (thinned) values in output_data.
- n_end
The last iteration in the original MCMC chain to use in the calculations. Assumed to be the
total number of iterations performed, i.e. n_iter, if not given.
- plot_pretty
logical, defaulting to TRUE. If set TRUE then will select pretty plotting
margins (that create sufficient space for axis titles and rotates y-axis labels). If FALSE will
implement current user values.
- plot_lwd
The line width to use when plotting the posterior mean (and confidence intervals).
Default is 2 (to add emphasis).