jaccard.index: Jaccard Index similarity coefficient

In ialmodovar/RFASTfMRI: FAST Adaptive Smoothing and Thresholding for Improved Activation Detection in Low-Signal fMRI

Description

Compute Jaccard index to determine similarity between activation maps.

Usage

jaccard.index(x, y)

Arguments

x	vector of 0 and 1.
y	vector of 0 and 1.

Details

x and y need to be of the same size. NA will be automatically remove. Value close to 1 means excellent similarity while value close to 0 vector are different

Author(s)

Israel Almodovar-Rivera and Ranjan Maitra.

References

Almodovar-Rivera, I., & Maitra, R. (2019). FAST adaptive smoothing and thresholding for improved activation detection in low-signal fMRI. IEEE transactions on medical imaging, 38(12), 2821-2828.

Maitra, R. (2010). A re-defined and generalized percent-overlap-of-activation measure for studies of fMRI reproducibility and its use in identifying outlier activation maps. Neuroimage, 50(1), 124-135.

Jaccard, P. (1901). Etude comparative de la distribution florale dans une portion des Alpes et des Jura. Bull Soc Vaudoise Sci Nat, 37, 547-579.

Examples

## Not run: 
set.seed(787)
x <- sample(x = 0:1,size = 50,replace=TRUE)
y <- sample(x = 0:1,size = 50,replace=TRUE)
jaccard.index(x = x,y = y)

## End(Not run)

ialmodovar/RFASTfMRI documentation built on Jan. 26, 2020, 4:02 a.m.