summarizeClusters: Descriptive statistics by group

In geocmeans: Implementing Methods for Spatial Fuzzy Unsupervised Classification

Descriptive statistics by group

Description

Calculate some descriptive statistics of each group

Usage

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)

geocmeans documentation built on Sept. 12, 2023, 9:06 a.m.