Summarize a mixture model

This function calculates posterior quantiles of parameters of a mixture model across all chains or for each chain separately

Usage

# S3 method for class 'mixglm'
summary(
  object,
  byChains = FALSE,
  digit = 4L,
  absInt = FALSE,
  randomSample = NULL,
  ...
)

Arguments

object

an object of class "mixglm"

byChains

logical value indicating if the summary should be calculated for each chain separately

digit

integer specifying the number of decimal places to be used. Use "NULL" for no rounding.

absInt

logical value indicating if intercepts for state values should be absolute (by default, they represent differences)

randomSample

integer specifying how many random samples from posterior distribution to take instead of summary. Use "NULL" for summary.

...

further arguments passed to or from other methods.

Value

Returns a list with one item being data.frame of quantiles of posterior distributions of parameters. If byChains is TRUE, a data.frame is returned for each chain.

Author

Adam Klimes

Examples

if (FALSE) { # \dontrun{
set.seed(10)
n <- 200
x <- rnorm(n)
group <- rbinom(n, 1, 0.5)
y <- rnorm(n, 1 + 0.5 * x * c(-1, 1)[group + 1], 0.1)
plot(y ~ x)
dat <- data.frame(x, y)

mod <- mixglm(
  stateValModels = y ~ x,
  stateProbModels = ~ x,
  statePrecModels = ~ x,
  inputData = dat,
  numStates = 2)
summary(mod)

# random samples of parameters from posterior distribution
summary(mod, randomSample = 5)} # }