Find.Clusters.TStg2: Find.Clusters.TStg2

In mkamenet3/coefclust: Clustered spatio-temporal varying coefficient regression modeling

Description

Find multiple clusters sequentially via Simulataneous detection. Find and test the cluster in the simple linear regression for given potential centroids via the 2nd stage in Two-stage detection: the same slope but different intercept.

Usage

Find.Clusters.TStg2(y, X, long, lat, MR, M, Cls1st, overlap, alpha)

Arguments

y	The input data(as a vector)
X	The input data(as a matrix)
long	longitude
lat	latitude
MR	Maximum radius
M	number of simulations
Cls1st	the output from Find.Clusters.TStg1 in the 1st-Stage
overlap	Boolean which is TRUE for overlapping clusters / FALSE for non-overlapping clusters
alpha	significance level

Value

list of cluster, coefficient, and indicator of cluster membership.

Examples

data("SE_FakeData")
y <- SE_FakeData$y
X <- cbind(rep(1,length(y)), SE_FakeData$x)
long <- SE_FakeData$long; lat <- SE_FakeData$lat
MR <- 300; M <- 2
Clusters_ts1 <- Find.Clusters.TStg1(y, X, long, lat, MR, M, overlap=TRUE, alpha=0.05)
Clusters_ts2 <- Find.Clusters.TStg2(y, X, long, lat, MR, M, Clusters_ts1, overlap=TRUE, alpha=0.05)

mkamenet3/coefclust documentation built on June 28, 2020, 10:41 a.m.