getClusterCt: Retrieve the Central Coordinates for Each Cluser after...

In sptemExp: Constrained Spatiotemporal Mixed Models for Exposure Estimation

Description

This function is the second step for Adaptive Kruskal algorithm for generating aggregate centers for Thiessen polygons with the aim to obtain the central point for each cluster.

Usage

getClusterCt(samples, clsInf)

Arguments

samples	Data frame for samples with the columns of coordinates (column name: x and y)
clsInf	Cluster results obtained from the fucntion,exeCluster

Details

Retrieve the central point for each cluster.

Value

vector format: coordinates (x and y) for each cluster

Author(s)

Lianfa Li [e-mail]

References

Thomas, C.; Leiserson, C.; Rivest, R.; Stein, C., Introduction To Algorithms (Third ed.). MIT Press: 2009

See Also

exeCluster, ~~~

Examples

samplePnt=data.frame(x=runif(100,1,100),y=runif(100,1,100))
clusterId=exeCluster(samplePnt,10)
clscenters=getClusterCt(samplePnt,clusterId)

sptemExp documentation built on July 7, 2019, 9:02 a.m.