I want to solve the following in R:
∫0H [π(t) ∫tH A(x) dx ] dt
Where π(t) is the prior and A(x) is the A function defined below.
prior <- function(t) dbeta(t, 1, 24)
A <- function(x) dbeta(x, 1, 4)
expected_loss <- function(H){
integrand <- function(t) prior(t) * integrate(A, lower = t, upper = H)$value
loss <- integrate(integrand, lower = 0, upper = H)$value
return(loss)
}
Since π(t), A(x) > 0, expected_loss(.5) should be less than expected_loss(1). But this is not what I get:
> expected_loss(.5)
[1] 0.2380371
> expected_loss(1)
[1] 0.0625
I'm not sure what I'm doing wrong.