plot_normal_normal {bayesrules} | R Documentation |
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.
plot_normal_normal( mean, sd, sigma = NULL, y_bar = NULL, n = NULL, prior = TRUE, likelihood = TRUE, posterior = TRUE )
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 |
a ggplot
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)