abc (version 1.5)

summary.abc: Summaries of posterior samples generated by ABC algortithms

Description

Calculates simple summaries of posterior samples: the minimum and maximum, the weighted mean, median, mode, and credible intervals.

Usage

## S3 method for class 'abc':
summary(object, unadj = FALSE, intvl = .95, print = TRUE,
digits = max(3, getOption("digits")-3), ...)

Arguments

object

an object of class "abc".

unadj

logical, if TRUE it forces to plot the unadjusted values when method is "loclinear" or "neuralnet".

intvl

size of the symmetric credible interval.

print

logical, if TRUE prints messages. Mainly for internal use.

digits

the digits to be rounded to. Can be a vector of the same length as the number of parameters, when each parameter is rounded to its corresponding digits.

...

other arguments passed to density.

Value

• The returned value is an object of class "table". The rows are,
• Min.
  minimun
• Lower perc.
  lower percentile
• Median
  or weighted median
• Mean
  or weighted mean
• Mode
  or weighted mode
• Upper perc.
  upper percentile
• Max.
  maximum

Details

If method is "rejection" in the original call to abc, posterior means, medians, modes and percentiles defined by intvl, 95 by default (credible intervals) are calculated. If a regression correction was used (i.e. method is "loclinear" or "neuralnet" in the original call to abc) the weighted posterior means, medians, modes and percentiles are calculated.

To calculate the mode, parameters are passed on from density.default. Note that the posterior mode can be rather different depending on the parameters to estimate the density.

See Also

abc, hist.abc, plot.abc

Examples

## see ?abc for examples