branch.and.bound.max.uncertainty: Computes the maximum uncertainty by a branch and bound...

In jeff-regier/MiniMiniMaxUQ: Mini-Minimax Uncertainty Quantification for Emulators

Description

Computes the maximum uncertainty by a branch and bound algorithm.

Usage

branch.and.bound.max.uncertainty(X, f.X, K.hat = NULL, tol = 0.001)

Arguments

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
tol	solutions this close to the maximum uncertainty are good enough. Defaults to 0.001.

Examples

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)
branch.and.bound.max.uncertainty(X, f.X, K.hat)

jeff-regier/MiniMiniMaxUQ documentation built on May 19, 2019, 1:45 a.m.