Commands are available form forming variograms and for producing kriged estimates.

`FVARIOGRAM` |
forms experimental variograms |
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`MVARIOGRAM` |
fits models to an experimental variogram |

`DVARIOGRAM` |
plots fitted models to an experimental variogram |

`KRIGE` |
calculates kriged estimates using a model fitted to a sample variogram |

`FCOVARIOGRAM` |
forms a covariogram structure containing auto-variograms of individual variates and cross-variograms for pairs from a list of variates |

`MCOVARIOGRAM` |
fits models to sets of variograms and cross-variograms |

`DCOVARIOGRAM` |
plots 2-dimensional auto- and cross-variograms |

`COKRIGE` |
calculates kriged estimates using a model fitted to the sample variograms and cross-variograms of a set of variates |

`KCROSSVALIDATION` |
computes cross validation statistics for punctual kriging |

`DHSCATTERGRAM` |
plots an h-scattergram |

Relevant procedures in the Library for spatial analyses include:

` ADJACENTCELLS` |
finds cells adjacent to other cells in a multi-dimensional array |
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`DKSTPLOT` |
produces diagnostic plots for space-time clustering |

`DPOLYGON` |
draws polygons using high-resolution graphics |

`DPTMAP` |
draws maps for spatial point patterns using high-resolution graphics |

`DPTREAD` |
adds points interactively to a spatial point pattern |

`DRPOLYGON` |
reads a polygon interactively from the current graphics device |

`DPSPECTRALPLOT` |
calculates an estimate of the spectrum of a spatial point pattern |

`FHAT` |
calculates an estimate of the F nearest-neighbour distribution function |

`FZERO` |
gives the F function expectation under complete spatial randomness |

`GHAT` |
calculates an estimate of the G nearest-neighbour distribution function |

`GRLABEL` |
randomly labels two or more spatial point patterns |

`GRTHIN` |
randomly thins a spatial point pattern |

`GRTORSHIFT` |
performs a random toroidal shift on a spatial point pattern |

`GRCSR` |
generates completely spatially random points in a polygon |

`KCSRENVELOPES` |
simulates K function bounds under complete spatial randomness |

`KHAT` |
calculates an estimate of the K function |

`KLABENVELOPES` |
gives bounds for K function differences under random labelling |

`KSED` |
calculates s.e. for K function differences under random labelling |

`KSTHAT` |
calculates an estimate of the K function in space, time and space-time |

`KSTMCTEST` |
performs a Monte-Carlo test for space-time interaction |

`KSTSE` |
calculates the standard error for the space-time K function |

`KTORENVELOPES` |
gives bounds for the bivariate K function under independence |

`K12HAT` |
calculates an estimate of the bivariate K function |

`MSEKERNEL2D` |
estimates the mean square error for a kernel smoothing |

`NEIGHBOURS` |
finds the neighbours of cells in a multi-dimensional array |

`PTAREAPOLYGON` |
calculates the area of a polygon |

`PTBOX` |
generates a box bounding or surrounding a spatial point pattern |

`PTCLOSEPOLYGON` |
closes open polygons |

`PTDESCRIBE` |
gives summary and second order statistics for a point process |

`PTGRID` |
generates a grid of points in a polygon |

`PTINTENSITY` |
calculates the overall density for a spatial point pattern |

`PTKERNEL2D` |
performs kernel smoothing of a spatial point pattern |

`PTK3D` |
performs kernel smoothing of space-time data |

`PTREMOVE` |
removes points interactively from a spatial point pattern |

`PTROTATE` |
rotates a point pattern |

`PTSINPOLYGON` |
returns points inside or outside a polygon |

`PTFCLUSTERS` |
forms clusters of points from their densities in multi-dimensional space |

`PTFILLCLUSTERS` |
fills holes within clusters of points in multi-dimensional space |