cf.tMSE: targeted Mean Squared Error criterion

In mludkov/mlOSP: Machine Learning and Regression Monte Carlo Algorithms for Optimal Stopping

targeted Mean Squared Error criterion

Description

tMSE for Contour Finding

Usage

cf.tMSE(objMean, objSd, seps = 0)

Arguments

objMean	predicted mean response
objSd	posterior standard deviation of the response
seps	epsilon in the tMSE formula. By default taken to be zero.

Details

compute predictive density at the contour, smoothed by seps

Author(s)

Mike Ludkovski

References

Mike Ludkovski, Kriging Metamodels and Experimental Design for Bermudan Option Pricing Journal of Computational Finance, 22(1), 37-77, 2018

X.Lyu, M Binois, M. Ludkovski (2020+) Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation <https://arxiv.org/abs/1807.06712>

See Also

[osp.seq.design]

mludkov/mlOSP documentation built on April 29, 2023, 7:56 p.m.