MultiHPD: Bayesian HPD regions for a series of MCMC chains

In ArchaeoPhases: Post-Processing of the Markov Chain Simulated by 'ChronoModel', 'Oxcal' or 'BCal'

Bayesian HPD regions for a series of MCMC chains

Description

Estimation of the highest posterior density regions for each variable of a simulated Markov chain. This function uses the hdr() function included in the hdrcde package. An HPD region may be a union of several intervals.

Usage

MultiHPD(data, position, level = 0.95, roundingOfValue = 0)

Arguments

data	Data frame containing the output of the MCMC algorithm.
position	Numeric vector containing the position of the column corresponding to the MCMC chains of interest.
level	Probability corresponding to the level of confidence.
roundingOfValue	Integer indicating the number of decimal places.

Details

Highest posterior density function region using the function hdr() from the hdrcd package

Value

Returns a matrix of values containing the level of confidence and the endpoints of each interval for each variable of the MCMC chain. The name of the resulting rows are the positions of the corresponding columns in the CSV file. The result is given in calendar years (BC/AD).

Author(s)

Anne Philippe, [e-mail] and

Marie-Anne Vibet, [e-mail]

References

Hyndman, R.J. (1996) Computing and graphing highest density regions. American Statistician, 50, 120-126.

Examples

  data(Events)
  MultiHPD(Events, c(2, 4, 3), 0.95)

ArchaeoPhases documentation built on June 22, 2022, 1:05 a.m.