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

View source: R/abc.R

summary.abcR Documentation

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.

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.

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

See Also

abc, hist.abc, plot.abc

Examples

## see ?abc for examples

abc documentation built on May 20, 2022, 1:11 a.m.