clusterSimmatrix {isocat}

Hierarchical clustering analysis of similarity matrix

Description

Function applies hierarchical clustering analysis to similarity matrix, such as one output by 'simmatrixMaker' function. Just a wrapper for pvclust. Output is a pvclust object.

Usage

clusterSimmatrix(
  simmatrix,
  dist_mthd = "correlation",
  hclust_mthd = "average",
  nBoot = 1000,
  nClusters = FALSE,
  r = seq(0.7, 1.4, by = 0.1)
)

Arguments

simmatrix

symmetric similarity matrix object.

dist_mthd

Distance measure to be used. Defaults to "correlation". See help(pvclust).

hclust_mthd

Method of clustering. Defaults to "average". See help(pvclust).

nBoot

number of bootstrap replications. Defaults to 1000. See help(pvclust).

nClusters

number of clusters to run in parallel using 'doParallel'. Defaults to FALSE (non-parallel).

r

Relative size of bootstrap replications.

Examples

# Create probability-of-origin maps to compare.
myiso <- rasterFromXYZ(isoscape)
raster::plot(myiso)
myiso_sd <- rasterFromXYZ(isoscape_sd)
n <- 5
set.seed(42)
df <- data.frame(
         ID = LETTERS[1:n],
         isotopeValue = sample(-120:-40, n),
         SD_indv = rep(5, n)
         )
assignmentModels <- isotopeAssignmentModel(
                        ID = df$ID,
                        isotopeValue = df$isotopeValue,
                        SD_indv = df$SD_indv,
                        precip_raster = myiso,
                        precip_SD_raster = myiso_sd,
                        nClusters = FALSE
                        )
raster::plot(assignmentModels)
# Compare maps with simmatrixMaker.
mymatrix <- simmatrixMaker(assignmentModels, nClusters = FALSE, csvSavePath = FALSE)
# Cluster similarity matrix.
clust_results <- clusterSimmatrix(mymatrix, dist_mthd = "correlation",
    hclust_mthd = "average", nBoot = 1000,  nClusters = FALSE,
    r = seq(.7,1.4,by=.1) )
clust_results