Coregionalization by Linear Combination of Nonorthogonal Components

By J. Vargas-Guzmán, A. Warrick, Donald E. Myers. 2002

31 citations recorded by the source corpus.

Subfields: Applied Mathematics, Economics and Econometrics, Environmental Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Mathematics

1. Martin Schlather
2. Alan E. Gelfand
3. William Kleiber
4. Mauricio A Álvarez
5. Neil D. Lawrence
6. Lorenzo Rosasco
7. Tilmann Gneiting
8. James W. Taylor

In Economics and Econometrics

1. Alan E. Gelfand
2. Martin Schlather
3. Marc G. Genton
4. Tilmann Gneiting
5. William Kleiber
6. Mikyoung Jun
7. Mauricio A Álvarez
8. Neil D. Lawrence

In Environmental Engineering

1. Alan E. Gelfand
2. Mikyoung Jun
3. Marc G. Genton
4. Martin Schlather
5. William Kleiber
6. Tilmann Gneiting
7. Tatiyana V. Apanasovich
8. Alexandra M. Schmidt

Citations in the corpus

• Kernels for Vector-Valued Functions: a Review (2011, methodology): “ues of d. Inference in this model is accomplished using Markov chain Monte Carlo. For details about the particular inference procedure, the reader is referred to [28]. A different extension is due to [33], in which the basic processes ui q(x) are assumed to be nonorthogonal, leading to the following”
• Matérn Cross-Covariance Functions for Multivariate Random Fields (2010, background): “The special case in which ν1 = ν2 = ν12 = 12 has been studied by Chilès and Delfiner (1999, p. 330), Vargas-Guzman, Warrick, and Myers (2002), and Wackernagel (2003, exercise 21.2).”
• Nonstationary multivariate process modeling through spatially varying coregionalization (2004, background): “Also, recent work of Vargas-Guzmán et al. (2002) allows the w(u)(s) hence the Y(u)(s) in (3.”