UMRhess: Compute Hessian of Unlinked Monotone Regression objective...
In UMR: Unmatched Monotone Regression

Compute Hessian of Unlinked Monotone Regression objective function from Balabdaoui, Doss, and Durot

1	UMRhess_generic(mm, ww_m, yy, ww_y = rep(1/length(yy), length(yy)), dens, BBp)

`mm`	Current (unsorted) estimate/iterate at which to compute gradient. (Length is <= than the number of X observations in the problem).
`ww_m`	Weights (nonnegative, sum to 1) corresponding to mm. Same length as mm.
`yy`	Y (response) observation vector (numeric)
`ww_y`	Weights (nonnegative, sum to 1) corresponding to yy. Same length as yy. Default is just 1/length(yy) for each value.
`dens`	This is the error density, a function object (Balabdaoui, Doss, Durot (2020+). Function accepting vector or matrix arguments.
`BBp`	This is derivative of "B" function ("B prime"), where B is defined in the paper. Function accepting vector or matrix arguments.