Altering the search neighborhood by changing the number of neighbors
The neighborhood search size defines the neighborhood shape and the constraints of the points within the neighborhood that will be used in the prediction of an unmeasured location.
You set the neighborhood parameters by looking for the locations of the points in the data view window and using prior knowledge gained in ESDA and semivariogram/covariance modeling.
The following are tips for altering the search neighborhood by changing the number of neighbors:
 Each sector will be projected outward if the minimum number of points is not found inside the sector.
 If there are no points within the searching neighborhood, then for most of the interpolation methods, it will mean that a prediction cannot be made at that location.
 Although some interpolators, such as simple and disjunctive kriging, predict values in areas without data points using the mean value of the dataset, a common practice is to change the searching neighborhood so that some points are located in the searching neighborhood.
Use the step below as a guide to changing the search neighborhood for any of the interpolation methods offered in Geostatistical Wizard (except for global polynomial interpolation). The step applies once you have defined the interpolation method and data you want to use and have advanced through the wizard until you have reached the Searching Neighborhood window.

Limit the number of neighbors to use for the prediction by changing the Maximum neighbors and Minimum neighbors parameters.
These parameter control the number of neighbors included in each sector of the search neighborhood. The number and orientation of the sectors can be changed by altering the Sector type parameter.
The impact of the search neighborhood can be assessed using the crossvalidation and comparison tools that are available in Geostatistical Analyst. If necessary, the search neighborhood can be redefined and another surface created.