clusterGrid_3D: Cluster analysis of 3D grids

In juanferngran/test: Visualizing climate4R data and Communicating Uncertainty in Seasonal Climate Prediction

Description

Performs cluster analysis of 3D grids. Several clustering algorithms are available.

Usage

clusterGrid_3D(grid, type, centers, iter.max, nstart, method)

Arguments

grid	A grid (gridded or station dataset), multigrid, multimember grid or multimember multigrid object, as returned e.g. by loadeR::loadGridData (or loadeR::loadStationData), a multigrid, as returned by makeMultiGrid, or other types of multimember grids (possibly multimember grids) as returned e.g. by loadeR.ECOMS::loadECOMS.
type	Clustering algorithm to be used for the cluster analysis. Possible values are "kmeans" (default), "hierarchical", "som". The core functions are kmeans, hclust, som, respectively. See Details.
centers	Integer value indicating the number of clusters, k, or center points. See Details.
iter.max	(for the K-means algorithm) Integer value indicating the maximum number of iterations allowed. Default: 10.
nstart	(for the K-means algorithm) If centers is a number, how many random sets should be chosen? Default: 1.
method	(for the hierarchical algorithm) Agglomeration method to be used, one of "complete" (default), "ward.D", "ward.D2", "single", "average", "mcquitty", "median" or "centroid".

Value

A new 3D grid object that contains the clusters created using the specified algorithm. The clustering type, number of clusters and other algorithm-specific parameters are provided as attributes.

juanferngran/test documentation built on June 29, 2020, 3:11 a.m.