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The G3GRID Procedure |
About the Input Data Set |
The input data set must contain at least three numeric variables:
The procedure can process multiple vertical variables for each pair of horizontal variables that you specify. If you specify more than one vertical variable, the G3GRID procedure performs a separate analysis and produces interpolated or smoothed values for each vertical variable. If more than one observation in the input data set has the same values for both horizontal variables, x and y, a warning message is printed, and only the first such point is used in the interpolation.
By default, the interpolation is performed after both variables are similarly scaled because the interpolation methods assume that the scales of x and y are comparable.
Multiple Vertical Variables |
Horizontal Variables Along a Nonlinear Curve |
If the horizontal variable points are collinear, the procedure interpolates the function as constant along lines perpendicular to the line in the plane that is generated by the input data points.
About the Output Data Set |
You can control both the number of x and y values in the output data set and the values themselves. In addition, you can specify an interpolation method.
Interpolation Methods |
This default method of interpolation works best for fairly smooth functions with values given at uniformly distributed points in the plane. If the data points in the input data set are erratic, the default interpolated surface can be erratic.
This default method is a modification of that described by Akima (1978). This method consists of
The coefficients for the polynomial are computed based on
The estimates of the first and second derivatives are
computed using the n nearest neighbors of the point, where n is the number specified in the GRID statement's NEAR= option. A
Delauney triangulation (Ripley 1981, p. 38) is used for the default method.
The coordinates of the triangles are available in an output data set if requested
by the OUTTRI= option in the PROC G3GRID statement.
The function u, formed when you specify the SPLINE option, is determined by letting
and
where
The coefficients c1, c2,..., cn and d1, d2, d3 of this polynomial are determined by these equations:
and
where
See Wahba (1979) for more detail.
To produce a smoothed spline, you can use the GRID statement's SMOOTH= option with the SPLINE option. The value or values specified in the SMOOTH= option are substituted for in the equation that is described in Spline Interpolation. A smoothed spline trades closeness to the original data points for smoothness. To find a value that produces the best balance between smoothness and fit to the original data, you can try several values for the SMOOTH= option.
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