grts.point: Draw a equi-probable GRTS sample from a discrete (point)...
In SDraw: Spatially Balanced Samples of Spatial Objects

Description Usage Arguments Details Value Author(s) References See Also Examples

Draws an equi-probable unstratified Generalized Random Tessellation Stratified (GRTS) sample from a SpatialPoints* object

1	grts.point(x, n, over.n = 0)

`x`	A `SpatialPoints` or `SpatialPointsDataFrame` object.
`n`	Sample size. The number of sample points to draw from `x`
`over.n`	Over-sample size. The number of 'over-sample' points to draw from `x`. The actual number of points drawn from `x` is `n + over.n`.

This is a wrapper for the grts function in package spsurvey. This simplifies calling grts when equi-probable samples are desired. It extends the valid input frame types to SpatialPoints objects (i.e., no attributes), rather than just SpatialPointsDataFrame objects. For more complicated designs (e.g., variable probability, stratification), call grts directly.

A SpatialPointsDataFrame containing locations in the GRTS sample, in order they are to be visited. Attributes of the sample points (in the embedded data frame) are as follows:

sampleID: Unique identifier for sample points. This encodes the GRTS ordering of the sample. The output object comes pre-sorted in GRTS order. If the sample becomes un-GRTS-ordered, resort by sampleID (i.e., samp <- samp[order(samp$sampleID),]).
pointType: A string identifying regular sample points (pointType=="Sample") and over-sample points (pointType=="OverSample").
geometryID: The ID of the point in x which was sampled. The ID of points in x are row.names( geometry(x)).
Any attributes of the original points (in x).

Trent McDonald

Stevens, D. L. and A. R. Olsen (1999). Spatially restricted surveys over time for aquatic resources. Journal of Agricultural, Biological, and Environmental Statistics 4 (4), 415-428.

Stevens, D. L. and A. R. Olsen (2004). Spatially balanced sampling of natural resources. Journal of the American Statistical Association 99, 262-278.

grts.line, grts.polygon, hip.point, sdraw

#   Draw sample
WA.city.samp <- grts.point(WA.cities,100,50)

#   Plot
plot( WA.cities, pch=16, cex=.5 )

# Plot 'sample' locations
plot( WA.city.samp[ WA.city.samp$pointType == "Sample", ], pch=1, add=TRUE, col="red" )  

# Plot 'over sample' locations
plot( WA.city.samp[ WA.city.samp$pointType == "OverSample", ], pch=2, add=TRUE, col="blue" )