| MultiHPD {RChronoModel} | R Documentation |
Bayesian highest posterior density regions for a series of MCMC chains
Description
Estimation of the highest posterior density regions for each variables of simulated Markov chain. This function uses the "hdr" function oincluded in the package "hdrcde.
Usage
MultiHPD(data, position, level=0.95)
Arguments
data |
dataframe 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 |
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.
Author(s)
Anne Philippe <Anne.Philippe@univ-nantes.fr> and
Marie-Anne Vibet <Marie-Anne.Vibet@univ-nantes.fr>
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)