You are currently viewing an archived version of Topic Semi-variogram modeling.
If updates or revisions have been published you can find them at Semi-variogram modeling.
Learning Objectives:
List the possible sources of error in a selected and fitted model of an experimental semi-variogram
Describe the conditions under which each of the commonly used semi-variograms models would be most appropriate
Explain the necessity of defining a semi-variogram model for geographic data
Apply the method of weighted least squares and maximum likelihood to fit semi-variogram models to datasets
You are currently viewing an archived version of Topic Semi-variogram modeling. If updates or revisions have been published you can find them at Semi-variogram modeling.
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