All other factors equal, the closer a data point is to a grid node, the more weight the weighted average interpolator gives it in determining the grid node value. There are two types of weighted average interpolators included in WinPICS.
Honors input data values exactly when data points coincide with grid nodes. Where data points do not coincide perfectly with grid nodes, grid node values are interpolated. You can increase the likelihood of your data being honored by increasing the grid density. The following gridding methods are exact interpolators:
Gives weight to neighboring data points, which smoothes out small anomalies. The user determines the amount of weight. The following gridding methods are examples of smoothing interpolators:
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