Probability and Bayesian Modeling
Bar plot of numeric or character data
Computes Posterior Probabilities for Discrete Models
Displays Areas Under a Beta Curve
Simulate random data from a beta curve
Draw a Beta Curve
Probability Interval for a Beta Curve
Plot of Two Beta Curves
Displays a Quantile of a Beta Curve
Centers title in a ggplot2 graphic
Shiny App to Choose a Beta Curve
Plot of Distribution of Two Proportions
Hypergeometric sampling density
Computes likelihoods for spinner outcomes
Gibbs sampling of the beta-binomial distribution
Gibbs sampling of a bivariate discrete distribution
Gibbs sampling of the normal sampling posterior
Graduate School Admission
Increases font size of text
JAGS Script for Common Models
Graph of several normal curves
Graphs a collection of spinners
Metropolis sampling of a continuous distribution
Displays Area Under a Normal Curve
Draws a Normal Curve
Probability Interval for a Normal Curve
Displays a Quantile of a Normal Curve
Updates a Normal Prior with Normal Data
Graphs prior and posterior probabilities
Constructs a graph of a probability distribution
Metropolis sampling of a discrete distribution
Implements Bayes' rule for a spinner problem
Simulate random data from a spinner
Computes likelihood matrix for many spinners
Constructs a spinner
Display probability distribution for a spinner
Testing prior for two proportions
Summaries of a probability matrix
Posterior updating of two proportions
Functions and datasets to accompany J. Albert and J. Hu, "Probability and Bayesian Modeling", CRC Press, (2019, ISBN: 1138492566).