ggdmc (version 0.2.5.2)

summary.model: Summarise posterior samples

Description

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

Usage

# S3 method for 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

summarise from which iteration.

end

summarise to the end 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 indicating 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_one(hsam[[1]], 1, 100, c(.025, .5, .975), verbose = TRUE)
est4 <- summary_one(hsam[[1]], 1, 100, c(.025, .5, .975), verbose = F)

est5 <- summary_many(hsam, 1, 100, c(.025, .5, .975), FALSE)
est6 <- summary_many(hsam, 1, 100, c(.025, .5, .975), TRUE)
est7 <- summary(hsam)
est8 <- summary(hsam, verbose = TRUE)
est9 <- summary(hsam, verbose = FALSE)


hest1 <- summary_hyper(hsam, 1, 100, F, F, c(.025, .5, .975), 2, F)
hest2 <- summary_hyper(hsam, 1, 100, F, F, c(.05, .5, .9), 2, F)
hest3 <- summary(hsam, TRUE)
# }