spatialEco (version 0.1-7)

separability: separability

Description

Calculates variety of univariate or multivariate separability metrics for two class samples

Usage

separability(x, y, plot = FALSE, cols = c("red", "blue"),
  clabs = c("Class1", "Class2"), ...)

Arguments

x

X vector

y

Y vector

plot

plot separability (TRUE/FALSE)

cols

colours for plot (must be equal to number of classes)

clabs

labels for two classes

...

additional arguments passes to plot

Value

A data.frame with the following separability metrics: B Bhattacharryya distance statistic JM Jeffries-Matusita distance statistic M M-Statistic D Divergence index TD Transformed Divergence index

References

Anderson, M. J., & Clements, A. (2000) Resolving environmental disputes: a statistical method for choosing among competing cluster models. Ecological Applications 10(5):1341-1355 Bhattacharyya, A. (1943) On a measure of divergence between two statistical populations defined by their probability distributions'. Bulletin of the Calcutta Mathematical Society 35:99-109 Bruzzone, L., F. Roli, S.B. Serpico (1995) An extenstion to multiclass cases of the Jefferys-Matusita distance. IEEE Transactions on Pattern Analysis and Machine Intelligence 33:1318-1321 Du, H., C.I. Chang, H. Ren, F.M. D'Amico, J. O. Jensen, J., (2004) New Hyperspectral Discrimination Measure for Spectral Characterization. Optical Engineering 43(8):1777-1786. Kailath, T., (1967) The Divergence and Bhattacharyya measures in signal selection. IEEE Transactions on Communication Theory 15:52-60 Kaufman Y., and L. Remer (1994) Detection of forests using mid-IR reflectance: An application for aerosol studies. IEEE T. Geosci.Remote. 32(3):672-683.

Examples

   norm1 <- dnorm(seq(-20,20,length=5000),mean=0,sd=1) 
   norm2 <- dnorm(seq(-20,20,length=5000),mean=0.2,sd=2)                          
     separability(norm1, norm2) 
           
   s1 <- c (1362,1411,1457,1735,1621,1621,1791,1863,1863,1838)
   s2 <- c (1362,1411,1457,10030,1621,1621,1791,1863,1863,1838)
     separability(s1, s2, plot=TRUE)