Packaged: 2020-07-11 23:03:04 UTC; marlygotti

Packaged: 2020-05-15 02:48:39 UTC; marlygotti

person("Marly", "Gotti", , "marlygotti@gmail.com", role = c("aut", "cre")),
person("Max", "Kuhn", , "max@rstudio.com", role = "aut"),
Description: A modeling package compiling applicability domain methods in
R. It combines different methods to measure the amount of
extrapolation new samples can have from the training set. See Gadaleta et
Imports: dplyr, glue, hardhat (>= 0.1.2), Matrix, proxyC, purrr, rlang,
Suggests: covr, isotree, knitr, modeldata, recipes (>= 0.1.7),
rmarkdown, spelling, testthat (>= 3.0.0), xml2

Title: Amyloid Propensity Prediction Neural Network
Author: Carlos Família, Sarah R. Dennison, Alexandre Quintas, David A. Phoenix
Description: Amyloid propensity prediction neural network (APPNN) is an amyloidogenicity propensity predictor based on a machine learning approach through recursive feature selection and feed-forward neural networks, taking advantage of newly published sequences with experimental, in vitro, evidence of amyloid formation.
Packaged: 2015-07-12 15:56:23 UTC; carlosfamilia

Title: Approximate and Exact Optimal Transport Methods
Description: R and C++ functions to perform exact and
approximate optimal transport. All C++ methods are linkable
to other R packages via their header files.
LinkingTo: Rcpp, RcppEigen, RcppCGAL, BH
Suggests: testthat (>= 2.1.0), transport

Title: Bayesian prediction of complex computer codes
Depends: R (>= 2.0.0), mvtnorm, adapt, emulator
Description: Performs Bayesian prediction of complex computer codes
when fast approximations are available: M. C. Kennedy and A.

when fast approximations are available: M. C. Kennedy and A. O'Hagan

Title: Bayesian Prediction of Complex Computer Codes
Description: Performs Bayesian prediction of complex computer codes when fast approximations are available.  It uses a hierarchical version of the Gaussian process, originally proposed by Kennedy and O'Hagan (2000), Biometrika 87(1):1.

Title: Approximately Optimal Fine Balance Matching with Multiple Groups
Description: Tools for constructing a matched design with multiple comparison groups.
Further specifications of refined covariate balance restriction and exact match on
covariate can be imposed. Matches are approximately optimal in  the sense that the
cost of the solution is at most twice the optimal cost, Crama and Spieksma (1992)