On the equivalence of kriging and maximum entropy estimators

Amorocho, J., and Espildora, B., 1973, Entropy in the assessment of uncertainty in hydrologic systems and models: Water Resources Res., v. 9, no. 6, p. 1511–1522.

Andricevic, R., and Foufoula-Georgiou, E., 1991, A transfer function approach to sampling network design for ground water contamination: Water Resources Res., v. 27, no. 10, p. 2759–2770.

Bras, R. L., and Rodriguez-Iturbe, I., 1985, Random functions and hydrology: Addison-Wesley Publ. Co., Reading, Massachusetts, 559 p.

Caselton, W. F., and Husain, T., 1980, Hydrologic networks: information transmission: Jour. Water Resource Planning and Management Division, ASCE, v. 106, no. WR2, p. 503–520.

Chapman, T. G., 1986, Entropy as a measure of hydrologie data uncertainty and model performance: Jour. Hydrology, v. 85, no. 1/2, p. 111–126.

Christakos, G., 1990, A Bayesian/maximum-entropy view to the spatial estimation problem: Math. Geology, v. 22, no. 7, p. 763–777.

Christakos, G., 1991, Some applications of the Bayesian/maximum-entropy concepts in geostatistics,in Grandy, W. T., and Schick, L. H., eds., Maximum entropy and bayesian methods: Kluwer Acad. Publ., Dordrecht, The Netherlands, p. 215–229.

Christakos, G., 1992, Random field models in earth sciences: Academic Press, San Diego, California, 474 p.

Christakos, G., and Olea, R. A., 1992, Sampling design for spatially distributed hydrogeologic and environmental processes: Advances in Water Resources, v. 15, no. 14, p. 219–238.

Christensen, R., 1991, Linear models for multivariate time series, and spatial data: Springer-Verlag, New York, 317 p.

Cressie, N., 1990, The origins of kriging: Math. Geology, v. 22, no. 3, p. 239–252.

Cressie, N., 1993, Statistics for spatial data (revised ed.): John Wiley & Sons, New York, 900 p.

David, M., 1988, Handbook of applied advanced geostatistical ore reserve estimation: Elsevier Science Publ. Co., New York, 216 p.

de Marsily, G., 1985, Quantitative hydrogeology: Groundwater hydrology for engineers: Academic Press, Orlando, Florida, 440 p.

Dowd, P. A., 1982, Lognormal kriging—the general case: Math. Geology, v. 14, no. 15, p. 475–499.

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

Fedorov, V. V., 1972, Theory of optimal experiments: Academic Press, New York, 292 p. (Studden, W. J., and Klimko, E. M., translators).

Fedorov, V. V., 1988, Experimental design technique in the optimization of a monitoring network,in Fedorov, V. V., and Lanter, H., eds., Model-oriented data analysis: Springer-Verlag, Berlin, 238 p.

Fedorov, V. V., and Mueller, W., 1989, Comparison of two approaches in the optimal design of an observation network: Statistics, v. 20, no. 3, p. 339–351.

Harmancioglu, N., and Yevjevich, V., 1987, Transfer of hydrologic information among river points: Jour. Hydrology, v. 91, no. 1-2, p. 103–118.

Husain, T., 1989, Hydrologic uncertainty measure and network design: Water Resources Bull., v. 25, no. 3, p. 527–534.

Jaynes, E. T., 1957, Information theory and statistical mechanics: Physical Review, v. 106, no. 4, p. 620–630.

Jaynes, E. T., 1982, On the rationale of maximum-entropy methods: Proc. IEEE, v. 70, no. 9, p. 939–952.

Johnson, N. L., and Kotz, S., 1972, Distributions in statistics: continuous multivariate distributions: John Wiley & Sons, New York, 333 p.

Jones, D. S., 1979, Elementary information theory: Oxford Univ. Press, New York, 182 p.

Joumel, A. G., 1980, The lognormal approach to predicting local distribution of selective mining unit grades: Math. Geology, v. 12, no. 4, p. 285–303.

Joumel, A. G., 1989, Fundamentals of geostatistics in five lessons (short course presented at the 28th Intern. Geol. Congress): Am. Geophy. Union, Washington, D.C., 40 p.

Joumel, A. G., and Deutsch, C. V., 1993, Entropy and spatial disorder: Math. Geology, v. 25, no. 3, p. 329–355.

Joumel, A. G., and Huijbregts, Ch. J., 1978, Mining geostatistics: Academic Press, London, 600 P.

Kapur, J. N., 1989, Maximum-entropy models in science and engineering: John Wiley & Sons, New York, 635 p.

Kapur, J. N., and Kesavan, H. K., 1992, Entropy optimization principles with applications: Academic Press, Boston, Massachusetts, 408 p.

Kvålseth, T., 1982, Some information properties of the lognormal distribution: IEEE Trans. on Information Theory, v. IT-28, no. 6, p. 963–966.

Lindley, D. V., 1956, On the measure of the information provided by an experiment: Ann. Math. Statistics, v. 27, no. 4, p. 986–1005.

Matheron, G., 1963, Principles of geostatistics: Econ. Geology, v. 58, no. 8, p. 1246–1266.

Matheron, G., 1973, The intrinsic random functions and their applications: Advances in Applied Probability, v. 5, p. 438–468.

Rendu, J.-M. M., 1979, Normal and lognormal estimation: Math. Geology, v. 11, no. 4, p. 407–422.

Rivoirard, J., 1994, Introduction to disjunctive kriging and non-linear geostatistics: Clarendon Press, Oxford, 180 p.

Rouhani, S., 1985, Variance reduction analysis: Water Resources Res., v. 21, no. 6, p. 837–846.

Rouhani, S., and Fiering, M. B., 1986, Resilience of a statistical sampling scheme: Jour. Hydrology, v. 89, no. 1-2, p. 1–11.

Rouhani, S., and Hall, T. J., 1988, Geostatistical scheme for groundwater sampling: Jour. Hydrology, v. 103, no. 1-2, p. 85–102.

Sacks, J., and Schiller, S., 1988, Spatial designs,in Gupta, S. S., and Berger, J. O., eds., Statistical design theory and related topics IV-2: Springer-Verlag, New York, p. 385–399.

Shannon, C. E., 1948, A mathematical theory of communication: The Bell System Tech. Jour., v. 27, p. 379–423, 623–656. Reprintedin Claude Elwood Shannon Collected Papers (Sloane, N. J. and Wyner, A. D., eds., 1993): IEEE Press, p. 5–83.

Shewry, M. C., and Wynn, H. P., 1987, Maximum entropy sampling: Jour. Applied Statistics, v. 14, no. 2, p. 165–170.

Singh, V. P., 1989, Hydrologic modeling using entropy: Jour. Engineers, Civil Engineering Division, v. 70, no. CV2, p. 55–60.

Singh, V. P., Rajagopal, A. K., and Singh, K., 1986, Derivation of some frequency distributions using the principle of maximum entropy: Advances in Water Research, v. 9, no. 2, p. 91–106.

Singh, V. P., and Singh, K., 1985, Derivation of the gamma distribution by using the principle of maximum entropy: Water Resources Bull., v. 21, no. 6, p. 941–952.

Theil, H., and Fiebig, D. G., 1984, Exploiting continuity, maximum entropy estimation of continuous distributions: Ballinger Publ. Co., Cambridge, Massachusetts, 246 p.

Tribus, M., 1978, Thirty years of information theory,in Levine, R. D., and Tribus, M., eds., The maximum entropy formalism: The MIT Press, Cambridge, Massachusetts, 498 p.

Trujillo-Ventura, A., and Ellis, J. H., 1991, Multiobjective air pollution monitoring network design: Atmospheric Environment, v. 25A, no. 2, p. 469–479.

Vanmarcke, E., 1983, Random fields: analysis and synthesis: The MIT Press, Cambridge, Massachusetts, 382 p.

Wu, S., and Zidek, J. V., 1992, An entropy-based analysis of data from selected NAPD/NTN network sites for 1983–1986: Atmospheric Environment, v. 26A, no. 11, p. 2089–2103.