mean.Bolstad {Bolstad} | R Documentation |
Calculate the posterior mean of an object of class Bolstad
. If the
object has a member mean
then it will return this value otherwise it
will calculate \int_{-\infty}^{+\infty}\theta f(\theta|x).d\theta
using
linear interpolation to approximate the density function and numerical
integration where \theta
is the variable for which we want to do
Bayesian inference, and x
is the data.
## S3 method for class 'Bolstad'
mean(x, ...)
x |
An object of class |
... |
Any other arguments. This parameter is currently ignored but it could be useful in the future to deal with problematic data. |
The posterior mean of the variable of inference given the data.
# The useful of this method is really highlighted when we have a general
# continuous prior. In this example we are interested in the posterior mean of
# an normal mean. Our prior is triangular over [-3, 3]
set.seed(123)
x = rnorm(20, -0.5, 1)
mu = seq(-3, 3, by = 0.001)
mu.prior = rep(0, length(mu))
mu.prior[mu <= 0] = 1 / 3 + mu[mu <= 0] / 9
mu.prior[mu > 0] = 1 / 3 - mu[mu > 0] / 9
results = normgcp(x, 1, density = "user", mu = mu, mu.prior = mu.prior)
mean(results)