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The intrinsic random functions and their applications
Open accessAbstract
The intrinsic random functions (IRF) are a particular case of the Guelfand generalized processes with stationary increments. They constitute a much wider class than the stationary RF, and are used in practical applications for representing non-stationary phenomena. The most important topics are: existence of a generalized covariance (GC) for which statistical inference is possible from a unique realization; theory of the best linear intrinsic estimator (BLIE) used for contouring and estimating problems; the turning bands method for simulating IRF; and the models with polynomial GC, for which statistical inference may be performed by automatic procedures.
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Cited by
On conditional and intrinsic autoregressions
BESAG, J., & KOOPERBERG, C. (1995) · Biometrika · doi:10.1093/biomet/82.4.733 · Cited by 732
Lv, Z., Lu, Z., & Wang, P. (2015) · Computers & Mathematics with Applications · doi:10.1016/j.camwa.2015.07.004 · Cited by 398
Mapping temperature using kriging with external drift: Theory and an example from scotland
Hudson, G., & Wackernagel, H. (1994) · International Journal of Climatology · doi:10.1002/joc.3370140107 · Cited by 342
Worden, K., & Cross, E. J. (2018) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2017.04.022 · Cited by 135
“Furthermore, because the confidence intervals are estimated from the Kriging means and variances, they are symmetric about the mean estimate.”
BackgroundInfluentialFree Energy Surface Reconstruction from Umbrella Samples Using Gaussian Process Regression
Stecher, T., Bernstein, N., & Csányi, G. (2014) · Journal of Chemical Theory and Computation · doi:10.1021/ct500438v · Cited by 56
Metadata
- Authors
- Matheron, G.
- Venue
- Advances in Applied Probability
- Publisher
- Cambridge University Press
- Published
- 1973-12-01
- Volume
- 5
- Issue
- 03
- Pages
- 439-468
- ISSN
- 0001-8678 (ISSN-L)
- OpenAlex
- W2056894411
- Cited by
- 1,498
- References
- 0
- FWCI
- 14.90
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Matheron, G. (1973). The intrinsic random functions and their applications. Advances in Applied Probability. https://doi.org/10.1017/s0001867800039379
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
