meanAggregateClusterProbability {isocat} | R Documentation |
Create mean aggregate probability-of-origin surfaces for each cluster.
Description
Subset probability-of-origin surfaces by cluster assignment and find mean aggregate probability-of-origin surface for each clustered group.
Usage
meanAggregateClusterProbability(indivIDs, clusters, surfaces, nClust = FALSE)
Arguments
indivIDs |
Vector of individual ID variables corresponding to surface names. |
clusters |
Vector of cluster IDs, in an order corresponding to 'indivIDs'. |
surfaces |
Stack of probability-of-origin surfaces for all individuals. Object of class 'RasterStack.' |
nClust |
Create and apply a multi-core cluster for faster processing using 'raster' and 'parallel' packages. Defaults to 'FALSE' (i.e., no clustering). |
Examples
# Create and cluster example assignment surfaces.
myiso <- rasterFromXYZ(isoscape)
myiso_sd <- rasterFromXYZ(isoscape_sd)
df <- data.frame(
ID = LETTERS[1:9],
isotopeValue = seq(-120,-25,length.out = 9),
SD_indv = rep(5, 9)
)
assignmentModels <- isotopeAssignmentModel(
ID = df$ID,
isotopeValue = df$isotopeValue,
SD_indv = df$SD_indv,
precip_raster = myiso,
precip_SD_raster = myiso_sd,
nClusters = FALSE
)
mySimilarityMatrix <- simmatrixMaker(assignmentModels)
cS <- clusterSimmatrix(
simmatrix = mySimilarityMatrix,
r = seq(.7,1.4,by=.1)
)
# Cut clusters.
myheight <- 0.25
df$cluster <- dendextend::cutree(cS$hclust, h = myheight)
# Create mean aggregate surfaces.r p
meanSurfaces <- meanAggregateClusterProbability(
indivIDs = df$ID,
clusters = df$cluster,
surfaces = assignmentModels,
nClust = FALSE
)
[Package isocat version 0.3.0 Index]