# Single Nugget Kriging

arXiv: https://arxiv.org/abs/1507.05128 · HTML: https://mlsanity.com/paper/1507.05128/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Jul 2015.

## Built on by (most cited first, 1 of 1)

- [Noise Estimation in Gaussian Process Regression](https://mlsanity.com/paper/2206.09976/) (2022)

## Abstract (arXiv)

We propose a method with better predictions at extreme values than the standard method of Kriging. We construct our predictor in two ways: by penalizing the mean squared error through conditional bias and by penalizing the conditional likelihood at the target function value. Our prediction exhibits robustness to the model mismatch in the covariance parameters, a desirable feature for computer simulations with a restricted number of data points. Applications on several functions show that our predictor is robust to the non-Gaussianity of the function.