GISTools (version 1.0-1)

Computational Inference from Point Data: Bootstrap and Kernel Bootstrap from Points

Description

Operations for bootstrapping and kernel bootstrapping based on point data. bstrap.points sample n points with replacement from a sample - and jitter.points adds a Gaussian displacement to each point in a data set. Applying a jitter to a bootstrap effectively creates a kernel bootstrap operation.

Usage

jitter.points(pts,scl)
bstrap.points(pts)

Value

A SpatialPointsDataFrame - with either a sample without replacement or a replica of the input data with displacements.

Arguments

pts

A SpatialPointsDataFrame or sf - POINT object

scl

A scale parameter - basically the standard deviation of the random Gaussian displacement

Author

Chris Brunsdon, Binbin Lu

Examples

# \donttest{
data(newhaven)
plot(blocks)
for (i in 1:20) plot(jitter.points(breach,150),add=TRUE,pch=1,col='red')
# }