TOC: Total Operating Characteristic Curve and ROC Curve

Construction of the Total Operating Characteristic (TOC) Curve and the Receiver (aka Relative) Operating Characteristic (ROC) Curve for spatial and non-spatial data. The TOC method is a modification of the ROC method which measures the ability of an index variable to diagnose either presence or absence of a characteristic. The diagnosis depends on whether the value of an index variable is above a threshold. Each threshold generates a two-by-two contingency table, which contains four entries: hits (H), misses (M), false alarms (FA), and correct rejections (CR). While ROC shows for each threshold only two ratios, H/(H + M) and FA/(FA + CR), TOC reveals the size of every entry in the contingency table for each threshold (Pontius Jr., R.G., Si, K. 2014. <doi:10.1080/13658816.2013.862623>).

Package details

AuthorRobert G. Pontius <rpontius@clarku.edu>, Ali Santacruz, Amin Tayyebi, Benoit Parmentier, Kangping Si
MaintainerAli Santacruz <amsantac@unal.edu.co>
LicenseGPL-3
Version0.0-5
URL https://github.com/amsantac/TOC
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("TOC")

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TOC documentation built on July 1, 2020, 11:54 p.m.