summary {ArchaeoPhases}

Marginal Summary Statistics for Multiple MCMC Chains

Description

Calculates summary statistics of the output of the MCMC algorithm for multiple parameters. Results are given in calendar years (BC/AD).

Usage

## S4 method for signature 'MCMC'
summary(object, level = 0.95, calendar = getOption("ArchaeoPhases.calendar"))

## S4 method for signature 'PhasesMCMC'
summary(object, level = 0.95, calendar = getOption("ArchaeoPhases.calendar"))

Arguments

object

An MCMC or a PhasesMCMC object.

level

A length-one numeric vector giving the confidence level.

calendar

A TimeScale object specifying the target calendar (see calendar()).

Value

A data.frame where the rows correspond to the chains of interest and columns to the following statistics:

mean

The mean of the MCMC chain.

sd

The standard deviation of the MCMC chain.

min

Minimum value of the MCMC chain.

q1

First quantile of the MCMC chain.

median

Median of the MCMC chain.

q3

Third quantile of the MCMC chain.

max

Maximum value of the MCMC chain.

lower

Lower boundary of the credible interval of the MCMC chain at level.

upper

Upper boundary of the credible interval of the MCMC chain at level.

Author(s)

A. Philippe, M.-A. Vibet, T. S. Dye, N. Frerebeau

See Also

Other statistics: interval_credible(), interval_hdr(), sensitivity()

Examples

## Coerce to MCMC
eve <- as_events(mcmc_events, calendar = CE(), iteration = 1)

## Summary
summary(eve, calendar = CE())
summary(eve, calendar = BP())

## Plot events
plot(eve, calendar = CE(), interval = "credible", level = 0.68)
plot(eve, calendar = BP(), interval = "hdr", level = 0.68)
plot(eve[, 1], interval = "hdr")

## Compute phases
pha <- phases(eve, groups = list(B = c(2, 4), A = c(1, 3)))

## Summary
summary(pha, calendar = CE())
summary(pha, calendar = BP())

## Plot phases
plot(pha, calendar = BP())
plot(pha, succession = "hiatus")
plot(pha, succession = "transition")