summary.model: Summarise posterior samples

In ggdmc: Cognitive Models

Description

This calls seven different variants of summary function to summarise posterior samples

Usage

## S3 method for class 'model'
summary(object, hyper = FALSE, start = 1, end = NA,
  hmeans = FALSE, hci = FALSE, prob = c(0.025, 0.25, 0.5, 0.75,
  0.975), recovery = FALSE, ps = NA, type = 1, verbose = FALSE,
  digits = 2, ...)

Arguments

object	posterior samples
hyper	whether to summarise hyper parameters
start	start from which iteration.
end	end at which iteration. For example, set start = 101 and end = 1000, instructs the function to calculate from 101 to 1000 iteration.
hmeans	a boolean switch indicating to calculate mean of hyper parameters
hci	boolean switch; whether to calculate credible intervals of hyper parameters
prob	a numeric vector, indicating the quantiles to calculate
recovery	a boolean switch indicating if samples are from a recovery study
ps	true parameter values. This is only for recovery studies
type	calculate type 1 or 2 hyper parameters
verbose	print more information
digits	printing digits
...	other arguments

Examples

## Not run: 
est1 <- summary(hsam[[1]], FALSE)
est2 <- summary(hsam[[1]], FALSE, 1, 100)

est3 <- summary(hsam)
est4 <- summary(hsam, verbose = TRUE)
est5 <- summary(hsam, verbose = FALSE)

hest1 <- summary(hsam, TRUE)

## End(Not run)

ggdmc documentation built on May 2, 2019, 9:59 a.m.