hip.polygon: Draws a Halton Iterative Partition (HIP) sample from a...

In SDraw: Spatially Balanced Samples of Spatial Objects

Description

Draws a Halton Iterative Partition (HIP) sample from a SpatialPoints* object.

Usage

hip.polygon(x, n, bases = c(2, 3), J = c(8, 5))

Arguments

x	A SpatialPoints or SpatialPointsDataFrame object. This object must contain at least 1 point. x is the 2-dimensional point resource from which samples are taken.
n	Target sample size. Target number of locations to draw from the set of points contained in x. If the sample size returned is less than the desired sample size, increase n until the desired sample size is reached.
bases	2X1 vector of Halton bases. These must be co-prime.
J	A 2X1 vector of base powers. J[1] is for horizontal, J[2] for vertical dimension. J determines the size and shape of the smallest Halton boxes. There are bases[1]^J[1] vertical columns of Halton boxes over x's bounding box, and bases[2]^J[2] horizontal rows of Halton boxes over the bounding box, for a total of prod(bases^J) boxes. The dimension of each box is c(dx,dy)/ (bases^J), where c(dx,dy) are the horizontal and vertical extents of x's bounding box. If J=NULL (the default), J is chosen so that Halton boxes are as square as possible.

Details

A brief description of Halton Iterative Partition (HIP) sampling for polygons: Given a set of Halton Iterative Partition parameters x (SpatialPoints* object), n (sample size), bases, and J, a lattice of Halton boxes is constructed iteratively over the bounding box of the input points. This results in prod(bases^J) Halton boxes on the bounding box to cover all points in the point resource. The target should be one point per box, or prod(bases^J) == n. The Halton index of all boxes is computed and assigned to points that lie in each box. Finally, a random number between 0 and the largest Halton index is drawn, and the next n coordinates in the mapped real numbers are taken as the sample.

Value

A SpatialPoints* object containing locations in the HIP sample.

Additional attributes of the output object, beyond those which make it a SpatialPoints*, are:

• frame: Name of the input sampling frame.

• frame.type: Type of resource in sampling frame. (i.e., "polygon").

• sample.type: Type of sample drawn. (i.e., "HIP").

• J: Exponents of the bases used to form the lattice of Halton boxes. This is either the input J, or the J vector computed by halton.indices.

• bases: Bases of the Halton sequence used to draw the sample.

• hl.bbox: The bounding box around points in x used to draw the sample. See halton.indices.

Author(s)

Michael Kleinsasser, Aidan McDonald

See Also

hip.point, SDraw, bas.point

Examples

# Draw sample of cities in the state of Washington
data(WA)
samp <- hip.polygon( WA, 100, J = c(3,2))
  

SDraw documentation built on July 8, 2020, 6:23 p.m.