summarize_normal_normal {bayesrules} | R Documentation |
Summarize a Normal-Normal Bayesian model
Description
Consider a Normal-Normal Bayesian model for mean parameter \mu
with
a N(mean, sd^2) prior on \mu
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 summarizes the mean, mode, and variance of the
prior and posterior Normal models of \mu
.
Usage
summarize_normal_normal(mean, sd, sigma = NULL, y_bar = NULL, n = NULL)
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 |
Value
data frame
Examples
summarize_normal_normal(mean = 2.3, sd = 0.3, sigma = 5.1, y_bar = 128.5, n = 20)
[Package bayesrules version 0.0.2 Index]