broom (version 0.4.0)

mcmc_tidiers: Tidying methods for MCMC (Stan, JAGS, etc.) fits

Description

Tidying methods for MCMC (Stan, JAGS, etc.) fits

Usage

tidyMCMC(x, pars, estimate.method = "mean", conf.int = FALSE,
  conf.level = 0.95, conf.method = "quantile", droppars = "lp__", ...)
## S3 method for class 'rjags':
tidy(x, pars, estimate.method = "mean", conf.int = FALSE,
  conf.level = 0.95, conf.method = "quantile", ...)
## S3 method for class 'stanfit':
tidy(x, pars, estimate.method = "mean", conf.int = FALSE,
  conf.level = 0.95, conf.method = "quantile", droppars = "lp__", ...)

Arguments

x

an object of class "stanfit"

pars

(character) specification of which parameters to nclude

estimate.method

method for computing point estimate ("mean" or median")

conf.int

(logical) include confidence interval?

conf.level

probability level for CI

conf.method

method for computing confidence intervals ("quantile" or "HPDinterval")

droppars

Parameters not to include in the output (such as log-probability information)

...

unused

Examples

# Using example from "RStan Getting Started"
# https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started

model_file <- system.file("extdata", "8schools.stan", package = "broom")

schools_dat <- list(J = 8,
                    y = c(28,  8, -3,  7, -1,  1, 18, 12),
                    sigma = c(15, 10, 16, 11,  9, 11, 10, 18))

if (requireNamespace("rstan", quietly = TRUE)) {
  set.seed(2015)
  rstan_example <- stan(file = model_file, data = schools_dat,
                        iter = 100, chains = 2)
}

if (requireNamespace("rstan", quietly = TRUE)) {
  # the object from the above code was saved as rstan_example.rda
  infile <- system.file("extdata", "rstan_example.rda", package = "broom")
  load(infile)

  tidy(rstan_example)
  tidy(rstan_example, conf.int = TRUE)

  td_mean <- tidy(rstan_example, conf.int = TRUE)
  td_median <- tidy(rstan_example, conf.int = TRUE, estimate.method = "median")

  library(dplyr)
  library(ggplot2)
  tds <- rbind(mutate(td_mean, method = "mean"),
               mutate(td_median, method = "median"))

  ggplot(tds, aes(estimate, term)) +
    geom_errorbarh(aes(xmin = conf.low, xmax = conf.high)) +
    geom_point(aes(color = method))
}