Packaged: 2020-06-12 13:36:20 UTC; antoinebichat

person("Antoine", "Bichat", , "antoine.bichat@proton.me", role = c("aut", "cre"),
Description: Evaluates the performance of binary classifiers.  Computes
confusion measures (TP, TN, FP, FN), derived measures (TPR, FDR,
accuracy, F1, DOR, ..), and area under the curve.  Outputs are well
Packaged: 2022-08-16 14:20:06 UTC; antoinebichat

Title: Evaluating Individualized Treatment Rules
person("Michael Lingzhi", "Li", , "mlli@mit.edu", c("aut", "cre")),
person("Kosuke", "Imai", , "imai@harvard.edu", c("aut"))
Maintainer: Michael Lingzhi Li <mlli@mit.edu>
Description: A collection of statistical methods for evaluating individualized treatment rules under randomized data. The provided metrics include PAV (Population Average Value), PAPE (Population Average Prescription Effect), and AUPEC (Area Under Prescription Effect Curve). It also provides the tools to analyze individualized treatment rules under budget constraints. Imai and Li (2019) <arXiv:1905.05389>.

Description: Provides various statistical methods for evaluating Individualized Treatment Rules under randomized data. The provided metrics include Population Average Value (PAV), Population Average Prescription Effect (PAPE), Area Under Prescription Effect Curve (AUPEC). It also provides the tools to analyze Individualized Treatment Rules under budget constraints. Detailed reference in Imai and Li (2019) <arXiv:1905.05389>.

Packaged: 2021-07-07 18:52:46 UTC; Michael Li

Depends: stats, MASS (>= 7.0), quadprog (>= 1.0), Matrix (>= 1.0),

Authors@R: c(person(given = "Numerious Inc.",
role = c("cph", "fnd")),person("Trevor", "Olsen", email = "trevor@numerious.com", role =c("aut", "cre"))   )
Description: The purpose of this package is to generate trees and validate unverified code. Trees are made by parsing a statement into a verification tree data structure. This will make it easy to port the statement into another language. Safe statement evaluations are done by executing the verification trees.
Suggests: testthat, rmarkdown, knitr, tufte, microbenchmark