Spatial statistics

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

`FVARIOGRAM`	forms experimental variograms
`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
`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

Updated on February 7, 2023

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