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Unbiased stereological estimation of the surface area of gradient surface processes
Published online by Cambridge University Press: 01 July 2016
Abstract
An unbiased stereological estimator for surface area density is derived for gradient surface processes which form a particular class of non-stationary spatial surface processes. Vertical planar sections are used for the estimation. The variance of the estimator is studied and found to be infinite for certain types of surface processes. A modification of the estimator is presented which exhibits finite variance.
MSC classification
- Type
- Stochastic Geometry and Statistical Applications
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- Copyright
- Copyright © Applied Probability Trust 1998
Footnotes
Dedicated to Professor Mecke on his 60th birthday.
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