In rockclimber112358/MCLE: Package to robustly fit distributions

I've created a package with the new version of the MCLE code:

# Source the old code:
library(sn)
library(mnormt)
library(rbenchmark)
dir = "~/GitHub/Robust-Skew-t/"
source(paste0(dir, "sn-funct.R"))
source(paste0(dir, "modified_mst.pdev.grad.R"))
source(paste0(dir, "robust_ST_for_mandy.R"))

Now, we can perform a quick speed comparison:

mst = list(dev = MCLE:::devMST, grad = MCLE:::gradDevMST,
           paramList2Vec = MCLE:::paramList2VecMST,
           paramVec2List = MCLE:::paramVec2ListMST)
initialNew = list(xi = c(0, 0), Omega = diag(c(1, 1)),
                  alpha = c(0, 0), nu = 100)
initialOld = dplist2optpar(initialNew)
benchmark(
    {
        data = matrix(rnorm(10), ncol = 2)
        robustST(data, start = initialOld)
    },
    {
        data = matrix(rnorm(10), ncol = 2)
        MCLE::MCLE(data = data, dist = mst, initial = initialNew)
    }
)

And now, let's try it with a larger sample size:

benchmark(
    {
        data = matrix(rnorm(500), ncol = 2)
        robustST(data, start = initialOld)
    },
    {
        data = matrix(rnorm(500), ncol = 2)
        MCLE::MCLE(data = data, dist = mst, initial = initialNew)
    }, replications = 10)