2 code implementations • 8 Sep 2017 • Alexander Litvinenko, Ying Sun, Marc G. Genton, David Keyes
We use available measurements to estimate the unknown parameters (variance, smoothness parameter, and covariance length) of a covariance function by maximizing the joint Gaussian log-likelihood function.
Computation 62F99, 62P12, 62M30 G.3; G.4; J.2
1 code implementation • 25 Feb 2022 • Jian Cao, Joseph Guinness, Marc G. Genton, Matthias Katzfuss
Gaussian process (GP) regression is a flexible, nonparametric approach to regression that naturally quantifies uncertainty.
no code implementations • 9 Apr 2017 • Wenlin Dai, Marc G. Genton
We define an outlyingness matrix by extending directional outlyingness, an effective measure of the shape variation of curves that combines the direction of outlyingness with conventional depth.
no code implementations • 3 Dec 2020 • Fernando de S. Bastos, Wagner Barreto-Souza, Marc G. Genton
We show that the non-robustness of the Heckman model may be due to the assumption of the constant sample selection bias parameter rather than the normality assumption.
Selection bias Methodology
no code implementations • 20 Jun 2023 • Pratik Nag, Yiping Hong, Sameh Abdulah, Ghulam A. Qadir, Marc G. Genton, Ying Sun
Fitting a Gaussian process with a nonstationary Mat\'ern covariance is challenging.