plot_normal_normal: Plot a Normal-Normal Bayesian model

In bayesrules: Datasets and Supplemental Functions from Bayes Rules! Book

Description

Consider a Normal-Normal Bayesian model for mean parameter μ with a N(mean, sd^2) prior on μ and a Normal likelihood for the data. Given information on the prior (mean and sd) and data (the sample size n, mean y_bar, and standard deviation sigma), this function produces a plot of any combination of the corresponding prior pdf, scaled likelihood function, and posterior pdf. All three are included by default.

Usage

plot_normal_normal(
  mean,
  sd,
  sigma = NULL,
  y_bar = NULL,
  n = NULL,
  prior = TRUE,
  likelihood = TRUE,
  posterior = TRUE
)

Arguments

mean	mean of the Normal prior
sd	standard deviation of the Normal prior
sigma	standard deviation of the data, or likelihood standard deviation
y_bar	sample mean of the data
n	sample size of the data
prior	a logical value indicating whether the prior model should be plotted
likelihood	a logical value indicating whether the scaled likelihood should be plotted
posterior	a logical value indicating whether posterior model should be plotted

Value

a ggplot

Examples

plot_normal_normal(mean = 0, sd = 3, sigma= 4, y_bar = 5, n = 3)
plot_normal_normal(mean = 0, sd = 3, sigma= 4, y_bar = 5, n = 3, posterior = FALSE)

bayesrules documentation built on Sept. 25, 2021, 9:06 a.m.