# Fast, Easy, and Visual Bayesian Inference

## Documentation for package ‘causact’ version 0.5.5

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

%>% | The magrittr pipe
addPriorGroups | Group together latent parameters by prior distribution.
baseballData | Dataframe of 12,145 observations of baseball games in 2010 - 2014
beachLocDF | Dataframe where each row represents data about one of the 26 mile markers (fake) from mile 0 to mile 2.5 along the Ocean City, MD beach/boardwalk.
bernoulli | probability distributions
beta | probability distributions
binomial | probability distributions
carModelDF | Dataframe of 1000 (fake) observations of whether certain car buyers were willing to get information on a credit card speciailizing in rewards for adventure travellers.
categorical | probability distributions
cauchy | probability distributions
check_r_causact_env | Check if 'r-causact' Conda environment exists
chimpanzeesDF | Data from behavior trials in a captive group of chimpanzees, housed in Lousiana. From Silk et al. 2005. Nature 437:1357-1359 and further popularized in McElreath, Richard. Statistical rethinking: A Bayesian course with examples in R and Stan. CRC press, 2020. Experiment
chi_squared | probability distributions
corruptDF | Dataframe of 174 observations where information on the human developmet index (HDI) and the corruption perceptions index (CPI) both exist. Each observation is a country.
dagp_plot | Plot posterior distribution from dataframe of posterior draws.
dag_create | Create a graph object for drawing a DAG.
dag_diagrammer | Convert graph to Diagrammer object for visualization
dag_dim | Add dimension information to 'causact_graph'
dag_edge | Add edge (or edges) between nodes
dag_greta | Generate a representative sample of the posterior distribution
dag_merge | Merge two non-intersecting 'causact_graph' objects
dag_node | Add a node to an existing 'causact_graph' object
dag_numpyro | Generate a representative sample of the posterior distribution
dag_plate | Create a plate representation for repeated nodes.
dag_render | Render the graph as an htmlwidget
delivDF | 117,790 line items associated with 23,339 shipments.
dirichlet | probability distributions
distributions | probability distributions
exponential | probability distributions
gamma | probability distributions
gymDF | Dataframe of 44 observations of free crossfit classes data Each observation indicates how many students that participated in the free month of crossfit signed up for the monthly membership afterwards
houseDF | Dataframe of 1,460 observations of home sales in Ames, Iowa. Known as The Ames Housing dataset, it was compiled by Dean De Cock for use in data science education. Each observation is a home sale. See 'houseDFDescr' for more info.
houseDFDescr | Dataframe of 523 descriptions of data values from "The Ames Housing dataset", compiled by Dean De Cock for use in data science education. Each observation is a possible value from a variable in the 'houseDF' dataset.
install_causact_deps | Install causact's python dependencies like numpyro, arviz, and xarray.
inverse_gamma | probability distributions
laplace | probability distributions
lkj_correlation | probability distributions
logistic | probability distributions
lognormal | probability distributions
meaningfulLabels | Store meaningful parameter labels
multinomial | probability distributions
multivariate_normal | probability distributions
negative_binomial | probability distributions
normal | probability distributions
pareto | probability distributions
poisson | probability distributions
prodLineDF | Product line and product category assignments for 12,026 partID's.
rbern | The Bernoulli Distribution
schoolsDF | This example, often referred to as 8-schools, was popularized by its inclusion in Bayesian Data Analysis (Gelman, Carlin, & Rubin 1997).
setDirectedGraphTheme | Set DiagrammeR defaults for graphical models
student | probability distributions
ticketsDF | Dataframe of 55,167 observations of the number of tickets written by NYC precincts each day Data modified from https://github.com/stan-dev/stancon_talks/tree/master/2018/Contributed-Talks/01_auerbach which originally sourced data from https://opendata.cityofnewyork.us/
totalBeachgoersRepSample | A representative sample from a random variable that represents the annual number of beach goers to Ocean City, MD beaches on hot days. Think of this representative sample as coming from either a prior or posterior distribution. An example using this sample is can be found in The Business Analyst's Guide To Business Analytics at https://www.causact.com/.
uniform | probability distributions
weibull | probability distributions