choicealpha: Choice of the mixing parameter In chavent/ClustGeo: Hierarchical Clustering with Spatial Constraints

Description

This function calculates the proportion of inertia explained by the partitions in `K` clusters for a range of mixing parameters `alpha`. When the proportion of explained inertia calculated with `D0` decreases, the proportion of explained inertia calculated with `D1` increases. The plot of the two curves of explained inertia (one for `D0` and one for `D1`) helps the user to choose the mixing parameter `alpha`.

Usage

 `1` ```choicealpha(D0, D1, range.alpha, K, wt = NULL, scale = TRUE, graph = TRUE) ```

Arguments

 `D0` a dissimilarity matrix of class `dist`. The function `as.dist` can be used to transform an object of class `matrix` to object of class `dist`. `D1` an other dissimilarity matrix of class `dist`. `range.alpha` a vector of real values between 0 and 1. `K` the number of clusters. `wt` vector with the weights of the observations. By default, wt=NULL corresponds to the case where all observations are weighted by 1/n. `scale` if TRUE the two dissimilarity matrices are scaled i.e. divided by their max. `graph` if TRUE, two graphics (proportion and normalized proportion of explained inertia) are drawn.

Value

An object with S3 class "choicealpha" and the following components:

 `Q` a matrix of dimension `length(range.alpha)` times `2` with the proportion of explained inertia calculated with `D0` (first column) and calculated with `D1` (second column) `Qnorm` a matrix of dimension `length(range.alpha)` times `2` with the proportion of normalized explained inertia calculated with `D0` (first column) and calculated with `D1` (second column)

References

M. Chavent, V. Kuentz-Simonet, A. Labenne, J. Saracco. ClustGeo: an R package for hierarchical clustering with spatial constraints. Comput Stat (2018) 33: 1799-1822.

`plot.choicealpha`, `hclustgeo`
 ```1 2 3 4 5 6 7 8``` ```data(estuary) D0 <- dist(estuary\$dat) # the socio-demographic distances D1 <- as.dist(estuary\$D.geo) # the geographic distances between the cities range.alpha <- seq(0,1,0.1) K <- 5 cr <- choicealpha(D0,D1,range.alpha,K,graph=TRUE) cr\$Q # proportion of explained pseudo inertia cr\$Qnorm # normalized proportion of explained pseudo inertia ```