Computes the distribution of `g(x)` where `x` is an `mle` object.

By the invariance property of the MLE, if `x` is an `mle` object, then under the right conditions, asymptotically, `g(x)` is normally distributed, g(x) ~ normal(g(point(x)),sigma) where `sigma` is the variance-covariance of `f(x)`

Usage

# S3 method for mle
rmap(x, g, ..., n = 1000L, method = c("mc", "delta"))

Arguments

x

an `mle` object

g

a function

...

additional arguments to pass to the `g` function

n

number of samples to take to estimate distribution of `g(x)` if `method == "mc"`.

method

method to use to estimate distribution of `g(x)`, "delta" or "mc".

Details

We provide two different methods for estimating the variance-covariance of `f(x)`: method = "delta" -> delta method method = "mc" -> monte carlo method