Calculate some descriptive statistics of each group

summarizeClusters(data, belongmatrix, weighted = TRUE, dec = 3, silent = TRUE)

Arguments

data

The original dataframe used for the classification

belongmatrix

A membership matrix

weighted

A boolean indicating if the summary statistics must use the membership matrix columns as weights (TRUE) or simply assign each observation to its most likely cluster and compute the statistics on each subset (FALSE)

dec

An integer indicating the number of digits to keep when rounding (default is 3)

silent

A boolean indicating if the results must be printed or silently returned

Value

A list of length k (the number of group). Each element of the list is a dataframe with summary statistics for the variables of data for each group

Examples

data(LyonIris)
AnalysisFields <-c("Lden","NO2","PM25","VegHautPrt","Pct0_14","Pct_65","Pct_Img",
"TxChom1564","Pct_brevet","NivVieMed")
dataset <- sf::st_drop_geometry(LyonIris[AnalysisFields])
queen <- spdep::poly2nb(LyonIris,queen=TRUE)
Wqueen <- spdep::nb2listw(queen,style="W")
result <- SFCMeans(dataset, Wqueen,k = 5, m = 1.5, alpha = 1.5, standardize = TRUE)
summarizeClusters(dataset, result$Belongings)