filterOnDistance: Filter sample using a minimum distance.

In spbal: Spatially Balanced Sampling Algorithms

Filter sample using a minimum distance.

Description

The input parameter minRadius >= 0 is the minimum distance between any two points in the sample. My idea is to apply this condition to the points in the over-sample, result$overSample. Let's call these points x1, x2, ..., xB. Create a new set S = (x1). Starting from x1, we check if dist(S,x2) > minRadius. If it is, add x2 to S. For x3, we check if dist(S,x3) > minRadius, where dist is the smallest distance from a point in S to x3 (single linkage distance). If dist(S,x3) > minRadius, add x3 to S. Continue until you reach xB.

The distances are calculated as great circles over an oblate spheroid and the units are meters.

Usage

filterOnDistance(overSample, minRadius)

Arguments

overSample	A HIP sample.
minRadius	The minimum distance between any two points in the sample.

Details

Key points:

• result$minRadius is nonempty (it always contains x1). Hence, if the user chooses a crazy minRadius, they get one point.

• result$minRadius is a subset of result$overSample.

• The number of points in result$minRadius is random. That's fine!

• If they want n points and result$minRadius has less than n, too bad! They can reduce minRadius and/or increase the iterations parameter.

• If they want a sample with the minimum radius property, they use:

  • smp <- result$minRadius

  • sample <- smp[1:n,]

Value

S The set of points that are more than minRadius from each other.

Author(s)

Phil Davies.

spbal documentation built on April 4, 2025, 2:05 a.m.