The KRIGE2D Procedure
| PREDICT Statement |
- PREDICT | PRED | P predict-options ;
You can specify the following options in a PREDICT statement.
- MAXPOINTS=number
- MAXP=number
- MAX=number
specifies the maximum number of data points in a neighborhood. You specify this option in conjunction with the RADIUS= option. When the number of data points in the neighborhood formed at a given grid point by the RADIUS= option is greater than the MAXPOINTS= value, the RADIUS= value is decreased just enough to honor the MAXPOINTS= value unless you specify the NODECREMENT option. The default is to include all data points within the specified RADIUS= value. Neighborhoods with very large numbers of data points might lead to unnecessarily slow execution times and potential lack of memory issues, depending on the problem setup and your computational resources. In that case, you could use the MAXPOINTS= option to set a cap for your neighborhood size. For details about numerical considerations, see the section Computational Resources. Unless the RADIUS= option is also specified, when the MAXPOINTS= and NUMPOINTS= options are specified in the same PREDICT statement the MAXPOINTS= option is ignored.
- MINPOINTS=number
- MINP=number
- MIN=number
specifies the minimum number of data points in a neighborhood. You specify this option in conjunction with the RADIUS= option. When the number of data points in the neighborhood formed at a given grid point by the RADIUS= option is less than the MINPOINTS= value, the RADIUS= value is increased just enough to honor the MINPOINTS= value unless you specify the NOINCREMENT option. The default is MINPOINTS=20. When enough data are available, you might improve prediction if you increase this value. When the MINPOINTS= and NUMPOINTS= options are specified in the same PREDICT statement, the MINPOINTS= option is set to the value of NUMPOINTS=.
- NODECREMENT | NODECR
requests that the RADIUS= value not be decremented when the MAXPOINTS= value is exceeded at a grid point. This option is relevant only when you specify both a RADIUS= value and a MAXPOINTS= value. In this case, when the number of points in the neighborhood constructed from the RADIUS= specification is greater than the MAXPOINTS= value, the RADIUS= value is decremented enough to honor the MAXPOINTS= value, and the kriging system is solved for this grid point. If you specify the NODECREMENT option, no decrementing is done, prediction is skipped at this grid point, and a message is written to the log.
- NOINCREMENT | NOINCR
requests that the RADIUS= value not be incremented when the MINPOINTS= value is not met at a grid point. This option is relevant only when you specify both a RADIUS= value and a MINPOINTS= number. In this case, when the number of points in the neighborhood constructed from the RADIUS= specification is less than the MINPOINTS= value, the RADIUS= value is incremented enough to honor the MINPOINTS= value, and the kriging system is solved for this grid point. If you specify the NOINCREMENT option, no incrementing is done, prediction is skipped at this grid point, and a message is written to the log.
- NUMPOINTS=number
- NPOINTS=number
- NPTS=number
- NP=number
specifies the exact size of a neighborhood. This option is incompatible with all other PREDICT statement options that control the neighborhood; it must appear by itself. In particular, if you specify both NUMPOINTS= and the RADIUS= option in the same PREDICT statement, then RADIUS= is honored, instead. In this event the value of the MINPOINTS= option is set to NUMPOINTS=, and the value of the MAXPOINTS= option is set to default, regardless of whether these options have been specified or not. If you specify any of the MINPOINTS= or MAXPOINTS= option without the RADIUS= option in the same PREDICT statement as NUMPOINTS=, then the NUMPOINTS= option is honored.
- RADIUS=number
- R=number
specifies the radius to use in a local kriging regression. When you specify this option, a separate kriging system is solved at each grid point by finding the neighborhood of this grid point that consists of all data points within the distance specified by the RADIUS= value. Thus, you can avoid unnecessary computational burden in your analysis by specifying the RADIUS= value to include data points situated within the extent of your problem’s spatial correlation. For additional control on the neighborhood, see the MAXPOINTS= and MINPOINTS= options. When you specify the RADIUS= and NUMPOINTS= options in the same PREDICT statement, then RADIUS= is honored.
- VAR= variable-name
specifies the single numeric variable used in the kriging system.