corners.uncertainty.bound: Computes a lower bound on the maximum uncertainty by...
In jeff-regier/MiniMiniMaxUQ: Mini-Minimax Uncertainty Quantification for Emulators

Computes a lower bound on the maximum uncertainty by evaluating the pointwise error at corners of the domain.

1	corners.uncertainty.bound(X, f.X, K.hat, n = 5000, first.corner = 0)

`X`	a matrix whose rows are points where f is observed
`f.X`	a vector whose values are f evaluated at each row of X
`K.hat`	the empirical Lipschitz constant of f
`n`	the number of consecutive corners to consider. Defaults to 5000.
`first.corner`	the first corner to consider. Defaults to 0.

X <- expand.grid(1:9, 1:9) / 10
f <- function(x) sin(x[1]) + cos(x[2])
f.X <- apply(X, 1, f)
K.hat <- find.K.hat(X, f.X)
corners.uncertainty.bound(X, f.X, K.hat)