Approximates an empirical distribution with a theoretical one

fit_mle(d, x, ...)

## Arguments

d A probability distribution object such as those created by a call to Bernoulli(), Beta(), or Binomial(). A vector of data to compute the likelihood. Unused. Unevaluated arguments will generate a warning to catch mispellings or other possible errors.

## Value

A distribution (the same kind as d) where the parameters are the MLE estimates based on x.

## Examples


X <- Normal()

fit_mle(X, c(-1, 0, 0, 0, 3))#> Normal distribution (mu = 0.4, sigma = 1.51657508881031)