rice (version 2.2.0)

hpd: Calculate highest posterior density

Description

Calculate highest posterior density ranges of a calibrated distribution

Usage

hpd(
  calib,
  prob = 0.95,
  return.raw = FALSE,
  BCAD = FALSE,
  ka = FALSE,
  age.round = 0,
  prob.round = 1,
  every = 0.1,
  bins = 20,
  add.zeros = FALSE
)

Value

The highest posterior density ranges, as three columns: from age, to age, and the corresponding percentage(s) of the range(s)

Arguments

calib

The calibrated distribution, as returned from caldist()

prob

Probability range which should be calculated. Default prob=0.95.

return.raw

The raw data to calculate hpds can be returned, e.g. to draw polygons of the calibrated distributions. Defaults to return.raw=FALSE.

BCAD

Which calendar scale to use. Defaults to cal BP, BCAD=FALSE.

ka

Whether to report results in years (default) or as ka

age.round

Rounding for ages. Defaults to 0 decimals.

prob.round

Rounding for reported probabilities. Defaults to 1 decimal.

every

Yearly precision (defaults to 0.1, as a compromise between speed and accuracy).

bins

The number of bins required. Any distribution with fewer bins gets recalculated using 100 narrower bins.

add.zeros

Pad the distribution with zeros at both extremes. Can be useful for distributions with 'open endings'. Defaults to FALSE

Examples

hpd(caldist(130,20, bombalert=FALSE))
plot(tmp <- caldist(2450,50), type='l')
myhpds <- hpd(tmp)
abline(v=unlist(myhpds[,1:2]), col=4)