Abstract
The major difficulty with non stationary phenomena is the estimation of parameters. It is known that the simple and appealing model: variable = deterministic drift + random fluctuation stumbles on the problem of identification of the underlying covariance or variogram.
We show how statistical inference is made possible by adopting another model, where the function is defined only through linear quantities named “generalized increments”. The procedure has been automatized and renders kriging a tool of easy use.
Finally a brief justification is given for non-stationary conditional simulations.
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© 1976 D. Reidel Publishing Company, Dordrecht—Holland
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Delfiner, P. (1976). Linear Estimation of non Stationary Spatial Phenomena. In: Guarascio, M., David, M., Huijbregts, C. (eds) Advanced Geostatistics in the Mining Industry. NATO Advanced Study Institutes Series, vol 24. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-1470-0_4
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DOI: https://doi.org/10.1007/978-94-010-1470-0_4
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