The VARIOGRAM Procedure

Empirical Semivariogram Computation

Using the values of LAGDISTANCE=7 and MAXLAGS=10 computed previously, rerun PROC VARIOGRAM without the NOVARIOGRAM option in order to compute the empirical semivariogram. You specify the CL option in the COMPUTE statement to calculate the 95% confidence limits for the classical semivariance. The section COMPUTE Statement describes how to use the ALPHA= option to specify a different confidence level.

Also, you can request a robust version of the semivariance with the ROBUST option in the COMPUTE statement. PROC VARIOGRAM produces a plot that shows both the classical and the robust empirical semivariograms. See the details of the PLOTS option to specify different instances of plots of the empirical semivariogram. The following statements implement the preceding requests: 

proc variogram data=sashelp.thick outv=outv;
   compute lagd=7 maxlag=10 cl robust;
   coordinates xc=East yc=North;
   var Thick;
run;

Figure 109.6 displays the PROC VARIOGRAM output empirical semivariogram table for the preceding statements. The table displays a total of eleven lag classes, even though you specified MAXLAGS= 10. The VARIOGRAM procedure always includes a zero lag class in the computations in addition to the MAXLAGS classes you request with the MAXLAGS= option. Hence, semivariance is actually computed at MAXLAGS+1 lag classes; see the section Distance Classification for more details.

Figure 109.6: Output Table for the Empirical Semivariogram Analysis

Spatial Correlation Analysis with PROC VARIOGRAM

The VARIOGRAM Procedure
Dependent Variable: Thick

Empirical Semivariogram
Lag
Class 		Pair
Count 		Average
Distance 		Semivariance
Robust Classical Standard
Error 		95% Confidence Limits
0 7 2.64 0.028 0.034 0.018 0 0.069
1 82 7.29 0.210 0.394 0.061 0.273 0.514
2 138 14.16 1.008 1.179 0.142 0.901 1.458
3 169 21.08 3.018 2.799 0.304 2.202 3.396
4 205 27.93 4.811 4.602 0.455 3.711 5.493
5 213 35.17 5.990 5.928 0.574 4.802 7.054
6 214 42.20 8.104 7.518 0.727 6.094 8.943
7 250 48.78 7.533 7.221 0.646 5.955 8.487
8 247 56.16 8.066 7.195 0.647 5.926 8.464
9 281 62.89 8.279 6.845 0.577 5.713 7.976
10 250 69.93 8.144 6.358 0.569 5.243 7.472 




            

            


            
Figure 109.7 shows both the classical and robust empirical semivariograms. In addition, the plot features the approximate 95% confidence
               limits for the classical semivariance. The figure exhibits a typical behavior of the computed semivariance uncertainty, where
               in general the variance increases with distance from the origin at Distance=0. 
            

            
  

            


Figure 109.7:  Classical and Robust Empirical Semivariograms for Coal Seam Thickness Data

               

                  
Classical and Robust Empirical Semivariograms for Coal Seam Thickness Data

               

            

            


            
The needle plot in the lower part of the Figure 109.7 provides the number of pairs that were used in the computation of the empirical semivariance for each lag class shown. In
               general, this is a pairwise distribution that is different from the distribution depicted in Figure 109.4. First, the number of pairs shown in the needle plot depends on the particular criteria you specify in the COMPUTE
                statement of PROC VARIOGRAM. Second, the distances shown for each lag on the Distance axis are not the midpoints of the lag classes as in the pairwise distances plot, but rather the average distance from the
               origin Distance=0 of all pairs in a given lag class.