inst/doc/plotting-mcmc-draws.R

params <-
list(EVAL = TRUE)

## ---- SETTINGS-knitr, include=FALSE-------------------------------------------
stopifnot(require("knitr"))
library("bayesplot")
knitr::opts_chunk$set(
  dev = "png",
  dpi = 150,
  fig.asp = 0.618,
  fig.width = 5,
  out.width = "60%",
  fig.align = "center",
  comment = NA,
  eval = if (isTRUE(exists("params"))) params$EVAL else FALSE
)

## ----pkgs, include=FALSE------------------------------------------------------
library("ggplot2")
library("rstanarm")

## ---- eval=FALSE--------------------------------------------------------------
#  library("bayesplot")
#  library("ggplot2")
#  library("rstanarm")

## ----mtcars-------------------------------------------------------------------
head(mtcars) # see help("mtcars")

## ---- eval=FALSE--------------------------------------------------------------
#  # linear regression model using stan_glm
#  # using '~ .' to include all variables
#  fit <- stan_glm(mpg ~ ., data = mtcars, seed = 1111)
#  print(fit)

## ----stan_glm, include=FALSE--------------------------------------------------
fit <- stan_glm(mpg ~ ., data = mtcars, QR = TRUE, seed = 1111)

## ----print-fit, echo=FALSE----------------------------------------------------
print(fit)

## ----get-draws----------------------------------------------------------------
posterior <- as.array(fit)
dim(posterior)
dimnames(posterior)

## ----mcmc_intervals-----------------------------------------------------------
color_scheme_set("red")
mcmc_intervals(posterior, pars = c("cyl", "drat", "am", "sigma"))

## ----mcmc_areas---------------------------------------------------------------
mcmc_areas(
  posterior, 
  pars = c("cyl", "drat", "am", "sigma"),
  prob = 0.8, # 80% intervals
  prob_outer = 0.99, # 99%
  point_est = "mean"
)

## ----mcmc_hist, message=FALSE-------------------------------------------------
color_scheme_set("green")
mcmc_hist(posterior, pars = c("wt", "sigma"))

## ----mcmc_hist-transform, message=FALSE---------------------------------------
color_scheme_set("blue")
mcmc_hist(posterior, pars = c("wt", "sigma"),
          transformations = list("sigma" = "log"))

## ----mcmc_hist_by_chain, message=FALSE----------------------------------------
color_scheme_set("brightblue")
mcmc_hist_by_chain(posterior, pars = c("wt", "sigma"))

## ----mcmc_dens, message=FALSE-------------------------------------------------
color_scheme_set("purple")
mcmc_dens(posterior, pars = c("wt", "sigma"))

## ----mcmc_dens_overlay, message=FALSE-----------------------------------------
mcmc_dens_overlay(posterior, pars = c("wt", "sigma"))

## ----mcmc_violin--------------------------------------------------------------
color_scheme_set("teal")
mcmc_violin(posterior, pars = c("wt", "sigma"), probs = c(0.1, 0.5, 0.9))

## ----mcmc_scatter-------------------------------------------------------------
color_scheme_set("gray")
mcmc_scatter(posterior, pars = c("(Intercept)", "wt"), 
             size = 1.5, alpha = 0.5)

## ----mcmc_hex-----------------------------------------------------------------
# requires hexbin package
if (requireNamespace("hexbin", quietly = TRUE)) {
  mcmc_hex(posterior, pars = c("(Intercept)", "wt"))
}

## ----mcmc_pairs, message=FALSE------------------------------------------------
color_scheme_set("pink")
mcmc_pairs(posterior, pars = c("(Intercept)", "wt", "sigma"),
           off_diag_args = list(size = 1.5))

## ----mcmc_trace---------------------------------------------------------------
color_scheme_set("blue")
mcmc_trace(posterior, pars = c("wt", "sigma"))

## ----change-scheme------------------------------------------------------------
color_scheme_set("mix-blue-red")
mcmc_trace(posterior, pars = c("wt", "sigma"), 
           facet_args = list(ncol = 1, strip.position = "left"))

## ----viridis-scheme, eval=FALSE-----------------------------------------------
#  color_scheme_set("viridis")
#  mcmc_trace(posterior, pars = "(Intercept)")

## ----mcmc_trace_highlight-----------------------------------------------------
mcmc_trace_highlight(posterior, pars = "sigma", highlight = 3)

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bayesplot documentation built on Nov. 17, 2022, 1:08 a.m.