By: M L Stein
Prediction of a random field based on observations of the random field at some set of locations arises in mining, hydrology, atmospheric sciences, and geography. Kriging, a prediction scheme defined as any prediction scheme that minimizes mean squared prediction error among some class of predictors under a particular model for the field, is commonly used in all these areas of prediction. This book summarizes past work and describes new approaches to thinking about kriging.
From a review: GEODERMA "the book is written with great care and dedication. Soil geostatisticians that are not easily scared off by mathematics will find this book to be a rich source of inspiration for many years to come."
Introduction.- Properties of Random Fields.- Asymptotic Properties of Linear Predictors.- Equivalence of Gaussian Measures and Linear Prediction.- Integration of Random Fields.- Estimating Parameters of Autocovariance Functions.- Discussion.
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