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sorocs  

A Bayesian Semiparametric Approach to Correlated ROC Surfaces
View on CRAN: Click here


Download and install sorocs package within the R console
Install from CRAN:
install.packages("sorocs")

Install from Github:
library("remotes")
install_github("cran/sorocs")

Install by package version:
library("remotes")
install_version("sorocs", "0.1.0")



Attach the package and use:
library("sorocs")
Maintained by
Weimin Zhang
[Scholar Profile | Author Map]
First Published: 2020-03-13
Latest Update: 2020-03-13
Description:
A Bayesian semiparametric Dirichlet process mixtures to estimate correlated receiver operating characteristic (ROC) surfaces and the associated volume under the surface (VUS) with stochastic order constraints. The reference paper is:Zhen Chen, Beom Seuk Hwang, (2018) "A Bayesian semiparametric approach to correlated ROC surfaces with stochastic order constraints". Biometrics, 75, 539-550. <doi:10.1111/biom.12997>.
How to cite:
Weimin Zhang (2020). sorocs: A Bayesian Semiparametric Approach to Correlated ROC Surfaces. R package version 0.1.0, https://cran.r-project.org/web/packages/sorocs. Accessed 18 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited sorocs R package
View sorocs citation profile
Other R packages that sorocs depends, imports, suggests or enhances
Complete documentation for sorocs
Functions, R codes and Examples using the sorocs R package
Some associated functions: asrm . sorocs . 
Some associated R codes: sorocs.R .  Full sorocs package functions and examples
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