choose_kmax: Finding best segmentation with a different threshold S

In rpatin/segclust2d: Bivariate Segmentation/Clustering Methods and Tools

Finding best segmentation with a different threshold S

Description

Choosing optimal number of segment using Marc Lavielle's method. From Emilie Lebarbier. Method based on identifying breaks in the slope of the contrast.

Usage

choose_kmax(x, S = 0.75)

Arguments

x	segmentation-class object
S	threshold for choosing the number of segment. See adehabitatLT::chooseseg

Value

the optimal number of segment given threshold S.

Examples

## Not run: 
res.seg <- segmentation(df, coord.names = c("x","y"), Kmax = 30, lmin = 10)
# find the optimal number of segment according to Lavielle's criterium with a
# different threshold.
choose_kmax(res.seg, S = 0.60) 

## End(Not run)

rpatin/segclust2d documentation built on Sept. 10, 2022, 8:02 a.m.