The Matérn Model: A Journey Through Statistics, Numerical Analysis and Machine Learning-Reference-Cited by-同舟云学术

The Matérn Model: A Journey Through Statistics, Numerical Analysis and Machine Learning

Published:2024-08-01 Issue:3 Volume:39 Page:
ISSN:0883-4237
Container-title:Statistical Science
language:
Short-container-title:Statist. Sci.

Author:

Porcu Emilio¹,Bevilacqua Moreno²,Schaback Robert³,Oates Chris J.⁴

Affiliation:

1. Emilio Porcu is Professor, Department of Mathematics, Khalifa University, Abu Dhabi, The United Arab Emirates and Research Fellow, ADIA Lab, Abu Dhabi, The United Arab Emirates

2. Moreno Bevilacqua is Professor, Department of Statistics, Universidad Adolfo Ibanez, Santiago, Chile

3. Robert Schaback is Professor, Department of Mathematics, University of Göttingen, Göttingen, Germany

4. Chris J. Oates is Professor, School of Mathematics, Statistics & Physics, Newcastle University, Newcastle, UK

Publisher

Institute of Mathematical Statistics

Reference181 articles.

1. Chilès, J.-P. and Delfiner, P. (2012). Geostatistics: Modeling Spatial Uncertainty, 2nd ed. Wiley Series in Probability and Statistics. Wiley, Hoboken, NJ.

2. Mardia, K. V. and Marshall, R. J. (1984). Maximum likelihood estimation of models for residual covariance in spatial regression. Biometrika 71 135–146.

3. Guttorp, P. and Gneiting, T. (2006). Studies in the history of probability and statistics. XLIX. On the Matérn correlation family. Biometrika 93 989–995.

4. Kaufman, C. G. and Shaby, B. A. (2013). The role of the range parameter for estimation and prediction in geostatistics. Biometrika 100 473–484.

5. Schoenberg, I. J. (1938). Metric spaces and completely monotone functions. Ann. of Math. (2) 39 811–841.

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Compatibility of space‐time kernels with full, dynamical, or compact support;Mathematical Methods in the Applied Sciences;2024-08

2. Scalable Model-Based Gaussian Process Clustering;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Extending the generalized Wendland covariance model;Electronic Journal of Statistics;2024-01-01