Estimating variograms of soil properties by the method‐of‐moments and maximum likelihood

By R. M. Lark. 2000

187 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Civil and Structural Engineering, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/3ca598e78199b92c16aefbc9e6e05b327c6c5169

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In Artificial Intelligence

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Citations in the corpus

Approximating likelihoods for large spatial data sets (2004, methodology): “Lark (2000) noted that there have not been any efforts to date to evaluate the effect ofVecchia’s approximation to the likelihood on the resulting parameter estimates.”
Testing the performance of spatial interpolation techniques for mapping soil properties (2006, background): “…a separation distance of h (referred to as the lag) is half the average squared difference between the value at z(xi) and the value at z(xi + h) (Lark, 2000b): γ̂(h) = 1 2N(h) N(h)∑ i=1 [z(xi) − z(xi + h)]2 (1) where N(h) is the number of data pairs within a given class of distance and…”
Spatial designs and properties of spatial correlation: Effects on covariance estimation (2007, background): “The almost universally poor performance of both estimators when 1/φ = 3 is somewhat surprising (Table 4)—although both Lark (2000) and Zimmerman and Zimmerman (1991) seem to suggest that the ML estimates should be worse with a stronger spatial correlation.”
Optimized Sample Schemes for Geostatistical Surveys (2007, methodology): “The relative merits of the method of moments and maximum likelihood for estimating variograms are discussed by Lark (2000) .”
Modelling soil variation: past, present, and future (2001, methodology): “Much more has been written about the support and how it affects the Ž accuracy of predictions in soil science Heuvelink and Pebesma, 1999; Bierkens . et al., 2000; Lark, 2000c , but we cannot pursue the subject further here.”
Biogeographical patterns of soil molecular microbial biomass as influenced by soil characteristics and management (2011, unknown): “The existence of these spatial outliers justifies the use of robust geostatistics (Lark, 2000).”