# load dagitty, and hack to make it work (we hope) library(dagitty) dagitty("dag{}") # our favorite suite of packages library(brms) library(ggformula) # formula interface to ggplot2 library(R2jags) # use JAGS from R library(rstan) # use Stan from R library(ggmcmc) library(coda) # work with MCMC samples library(bayesplot) # plots related to Bayesian data analysis library(rethinking) # Statistical Rethinking library(CalvinBayes) # load after coda and bayesplot # part of tidyverse for data wrangling library(dplyr) library(tidyr) library(purrr) # Some customization. You can alter or delete as desired (if you know what you are doing). # rstan configuration -- as recommended by rstan # use as many cores as are available options(mc.cores = parallel::detectCores()) # To avoid recompilation of unchanged Stan programs, we recommend calling rstan_options(auto_write = TRUE) # this sets the black/white theme for plots. # you can change the base_size to control the size of the text elements in the plot theme_set(theme_bw(base_size = 8)) knitr::opts_chunk$set( error = TRUE, # display error message and keep going if there is an error tidy = FALSE, # display code as typed size = "small", # slightly smaller font for code fig.width = 3.0, # width of figures (can be overridden in individual chunks) fig.height = 2.0, # heights of figures (can be overridden in individual chunks) fig.show = "hold" # put all figures after all the code )
An example with a couple of plots. Notice that they appear after all of the code and are small enough to fit side-by-side.
gf_dhistogram( ~ age, data = mosaicData::HELPrct) gf_density( ~ age, data = mosaicData::HELPrct)
Here's a wider plot using fig.width = 6
:
gf_dhistogram( ~ age, data = mosaicData::HELPrct, binwidth = 1) %>% gf_dens()
Looks like we have a work-around for daggity:
dag <- dagitty("dag{A <- B -> C}") drawdag(dag) impliedConditionalIndependencies(dag)
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