The following statements are available in PROC VARIOGRAM:
The COMPUTE and COORDINATES statements are required. The MODEL and PARMS statements are hierarchical. If you specify a PARMS statement, it must follow a MODEL statement.
Table 98.1 outlines the options available in PROC VARIOGRAM classified by function.
Task |
Statement |
Option |
---|---|---|
Data Set Options |
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Specify input data set |
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Suppress normal display of results |
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Write autocorrelation weights information |
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Write distance histogram information |
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Write Moran scatter plot information |
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Write pairwise point information |
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Write spatial continuity measures |
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Specify the plot display and options |
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Specify a model data set with MODEL statement |
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Specify a model data set with PARMS statement |
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Declaring the Role of Variables |
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Specify variables to define analysis subgroups |
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Specify variable with observation labels |
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Specify the analysis variables |
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Specify the x, y coordinates in the DATA= data set |
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Controlling Continuity Measure Computations |
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Specify the confidence level |
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Specify the angle tolerances for angle classes |
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Compute autocorrelation statistics |
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Specify the bandwidths for angle classes |
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Compute the semivariance estimate variance |
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Specify the minimum distance that indicates any two distinct points are not collocated |
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Specify the basic lag distance |
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Specify the tolerance around the lag distance |
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Specify the maximum number of lags in computations |
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Specify the number of angle classes |
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Suppress computation of all continuity measures |
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Compute robust semivariance |
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Controlling Distance Histogram Data Set |
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Specify the distance histogram data set |
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Specify the number of histogram classes |
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Controlling Pairwise Information Data Set |
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Specify the pairwise data set |
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Specify the maximum distance for the pairwise data set |
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Controlling Semivariogram Model Fitting |
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Specify the item store to save correlation information |
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Specify the confidence level for fitting parameters |
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Specify fitted model ranking criteria |
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Compute parameters estimate limits |
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Specify a threshold to compare model fit quality |
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Specify a tolerance to use in model classification |
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Specify the type of semivariogram to fit |
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Specify a type with a functional form |
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Specify the model fitting method |
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Specify a minimal nugget effect if experimental semivariance is zero at first lag |
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Suppress model fitting |
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Specify the nugget effect for fitted model |
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Specify a range estimate for fitted model |
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Specify a range of lags to fit a model in |
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Specify a scale estimate for fitted model |
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Specify a Matérn smoothness estimate |
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Specify constant parameters in fitting |
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Specify fitting parameter lower bounds |
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Specify the upper limit for fitted scale |
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Specify no bounds for fitted parameters |
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Specify the fitting parameter upper bounds |
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Specify optimization process options |
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Fitting Output Tables Control Options |
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Request the approximate covariance matrix |
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Request the approximate correlation matrix |
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Request fit details for every candidate model |
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Request the gradient of the objective function in parameter estimates table |
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Threshold to switch a Matérn form to Gaussian |
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Suppress the iteration history table |