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The Correlation Bias for Two-Dimensional Simulations by Turning Bands

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Abstract

The turning bands method (TBM) generates realizations of isotropic Gaussian random fields by summing contributions from line processes. We consider two-dimensional simulations and study the correlation bias attributable to the use of only a finite number L of lines. Our analytical and numerical results confirm that the maximal bias is of order 1/L, and that L = 64 lines suffice for excellent covariance reproduction. The notorious banding observed in simulations with an insufficient number of lines is a related but different phenomenon and depends strongly on the choice of the line simulation technique. Clear-cut recommendations for the number of lines necessary to avoid the effect can only be based on practical experience with the specific code at hand.

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REFERENCES

  • Armstrong, M., and Dowd, P. A., eds., 1994, Geostatistical simulations: Kluwer, Dordrecht, 255 p.

    Google Scholar 

  • Bras, R. L., and Rodríguez-Iturbe, I., 1976, Evaluation of mean square error involved in approximating the areal average of a rainfall event by a discrete summation: Water Resources Res., v. 12, no. 2, p. 181–184.

    Google Scholar 

  • Brooker, P. I., 1985, Two-dimensional simulation by turning bands: Math. Geology, v. 17, no. 1, 81–90.

    Google Scholar 

  • Chilès, J.-P., 1977, Géostatistique des phénomènes non stationnaires: PhD thesis, Université de Nancy-I, Nancy, France, 152+vii p.

    Google Scholar 

  • Cody, W. J., Paciorek, K. A., and Thacher, H. C., 1970, Chebyshev expansions for Dawson's integral: Mathematics of Computation, v. 24, p. 171–178.

    Google Scholar 

  • Davis, J. D., and Rabinowitz, P., 1975, Methods of numerical integration: Academic Press, New York, 459 p.

    Google Scholar 

  • Deutsch, C. V., and Journel, A. G., 1992, GSLIB, Geostatistical software library and user's guide: Oxford University Press, New York, 340 p.

    Google Scholar 

  • Dietrich, C. R., 1995, A simple and efficient space domain implementation of the turning bands method: Water Resources Res., v. 31, no. 1, p. 147–156.

    Google Scholar 

  • Dowd, P. A., 1992, A review of recent developments in geostatistics: Computers & Geosciences, v. 17, no. 10, p. 1481–1500.

    Google Scholar 

  • Fenton, G. A., 1994, Error evaluation for three random-field generators: Jour. Eng. Mech., v. 120, no. 12, p. 2478–2497.

    Google Scholar 

  • Fleischer, W., Nagel, M., and Ostermann, R. (eds.), 1992, ISP' 91, Interaktive Datenanalyse mit ISP: Westarp Wissenschaften, Essen, 257 p.

    Google Scholar 

  • Gneiting, T., 1998, Closed form solutions of the two-dimensional turning bands equation: Math. Geology, v. 30, no. 4, 379–390.

    Google Scholar 

  • Gotway, C. A., 1994, The use of conditional simulation in nuclear-waste-site performance assessment (with discussion): Technometrics, v. 36, no. 2, p. 129–161.

    Google Scholar 

  • Journel, A. G., 1974, Geostatistics for conditional simulation of ore bodies: Econ. Geology, v. 69, no. 5, p. 673–687.

    Google Scholar 

  • Lantuéjoul, C., 1994, Non conditional simulation of stationary isotropic multigaussian random functions (with discussion), in M. Armstrong and P. S. Dowd, eds., Geostatistical simulations: Kluwer, Dordrecht, p. 147–184.

    Google Scholar 

  • Lee, Y.-M, and Ellis, J. H., 1997, Estimation and simulation of lognormal random fields: Computers & Geosciences, v. 23, no. 1, p. 19–31.

    Google Scholar 

  • MacLeod, A. J., 1993, Chebyshev expansions for modified Struve and related functions: Mathematics of Computation, v. 60, no. 202, p. 735–747.

    Google Scholar 

  • Mantoglou, A., and Wilson, J. L., 1982, The turning bands method for simulation of random fields using line generation by a spectral method: Water Resources Res., v. 18, no. 5, p. 1379–1394.

    Google Scholar 

  • Matheron, G., 1973, The intrinsic random functions and their applications: Adv. Appl. Probab., v. 5, p. 439–468.

    Google Scholar 

  • Tompson, A. F. B., Ababou, R., and Gelhar, L. W., 1989, Implementation of the three-dimensional turning bands random field generator: Water Resources Res., v. 25, no. 10, p. 2227–2243.

    Google Scholar 

  • Wackernagel, H., 1995, Multivariate geostatistics: Springer, Berlin, 256 p.

    Google Scholar 

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Gneiting, T. The Correlation Bias for Two-Dimensional Simulations by Turning Bands. Mathematical Geology 31, 195–211 (1999). https://doi.org/10.1023/A:1007561801981

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