Power-law correlations, related models for long-range dependence and their simulation

By Tilmann Gneiting. Journal of Applied Probability, 2000

89 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/61a921393699dceb2de95a6caee4c07b46ab33d9

How researchers see this paper

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

In Economics and Econometrics

1. Simon Michael Papalexiou
2. F. Serinaldi
3. Aurelio Fernández Bariviera
4. Rafal Weron
5. Jakub Nowotarski

In Finance

1. F. Serinaldi
2. Simon Michael Papalexiou
3. Vijay P. Singh
4. Aurelio Fernández Bariviera
5. M. Janga Reddy
6. Poulomi Ganguli
7. Shenglian Guo
8. B. De Baets

In Statistical and Nonlinear Physics

1. F. Serinaldi
2. Simon Michael Papalexiou

Citations in the corpus

• Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity (2020, methodology): “Specifically for one‐dimensional power‐type correlation structures, several other formulas have been proposed (e.g., Gneiting, 1999, 2000; Gneiting & Schlather, 2004; Martin & Walker, 1997).”