| MarginalStatistics {RChronoModel} | R Documentation |
Marginal summary statistics
Description
Gives a list of summary statistics resulting from the output of the MCMC algorithm for a one-parameter.
Usage
MarginalStatistics(a_chain, level = 0.95, max_decimal = 0)
Arguments
a_chain |
numeric vector containing the output of the MCMC algorithm for a one-parameter |
level |
probability corresponding to the level of confidence used for the credible interval and the highest density region |
max_decimal |
maximum number of decimal |
Details
The 100*level % HPD (highest posterior density) region is estimated using HDR function from Package 'hdrcde'.
Value
A matrix of values corresponding to the following summary statistics
title |
The title of the summary statistics |
mean |
The mean of the MCMC chain. Use of "mean" function. |
map |
The maximum a posteriori of the MCMC chain. Use of "hdr" function. |
sd |
The standard deviation of the MCMC chain. Use of "sd" function. |
Q1, median, Q3 |
The quantiles of the MCMC chain corresponding to 0.25, 0.50 and 0.75. Use of "quantile" function. |
CI |
The credible interval corresponding to the desired level. Use of "CredibleInterval" function. |
HPDR |
The highest posterior density regions corresponding to the desired level. Use of "hdr" function. |
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); attach(Events)
MarginalStatistics(Event.1)
MarginalStatistics(Event.2, level = 0.90)