Last data update: 2014.03.03

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Results 1 - 4 of 4 found.
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RcmdrPlugin.ROC : Rcmdr Receiver Operator Characteristic Plug-In PACKAGE

Package: RcmdrPlugin.ROC
Type: Package
Title: Rcmdr Receiver Operator Characteristic Plug-In PACKAGE
Authors@R: c(person("Daniel-Corneliu", "Leucuta", role = c("aut", "cre"), email = "danny.ldc@gmail.com"),
person("Mihaela", "Hedesiu", role = "ctb"),
person("Andrei", "Achimas", role = "ctb"),
person("Oana", "Almasan", role = "ctb")
)
Version: 1.0-18
Date: 2014-12-20
Author: Daniel-Corneliu Leucuta [aut, cre],
Mihaela Hedesiu [ctb],
Andrei Achimas [ctb],
Oana Almasan [ctb]
Maintainer: Daniel-Corneliu Leucuta <danny.ldc@gmail.com>
Depends: R (>= 2.10), Rcmdr (>= 1.7.0), ROCR, pROC, ResourceSelection
Description: Rcmdr GUI extension plug-in for Receiver Operator Characteristic tools from pROC and ROCR packages. Also it ads a Rcmdr GUI extension for Hosmer and Lemeshow GOF test from the package ResourceSelection.
License: GPL (>= 2)
Packaged: 2015-02-26 12:16:09 UTC; danny
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-02-26 16:46:50

● Data Source: CranContrib
● 0 images, 2 functions, 0 datasets
● Reverse Depends: 0

FRESA.CAD : Feature Selection Algorithms for Computer Aided Diagnosis

Package: FRESA.CAD
Type: Package
Title: Feature Selection Algorithms for Computer Aided Diagnosis
Version: 2.2.0
Date: 2016-03-11
Author: Jose Gerardo Tamez-Pena, Antonio Martinez-Torteya and Israel Alanis
Maintainer: Jose Gerardo Tamez-Pena <jose.tamezpena@itesm.mx>
Description: Contains a set of utilities for building and testing formula-based models (linear, logistic or COX) for Computer Aided Diagnosis/Prognosis applications. Utilities include data adjustment, univariate analysis, model building, model-validation, longitudinal analysis, reporting and visualization.
License: LGPL (>= 2)
Depends: Rcpp (>= 0.10.0), stringr, miscTools, Hmisc, pROC
LinkingTo: Rcpp, RcppArmadillo
Suggests: nlme, rpart, gplots, RColorBrewer, class, cvTools, glmnet, survival
Packaged: 2016-03-11 20:17:39 UTC; Jose Tamez
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2016-03-12 00:03:41

● Data Source: CranContrib
● 0 images, 38 functions, 0 datasets
● Reverse Depends: 0

bimixt : Estimates Mixture Models for Case-Control Data

Package: bimixt
Type: Package
Title: Estimates Mixture Models for Case-Control Data
Version: 1.0
Date: 2015-08-24
Author: Michelle Winerip, Garrick Wallstrom, Joshua LaBaer
Maintainer: Michelle Winerip <mwinerip@asu.edu>
Description: Estimates non-Gaussian mixture models of case-control data. The four types of models supported are binormal, two component constrained, two component unconstrained, and four component. The most general model is the four component model, under which both cases and controls are distributed according to a mixture of two unimodal distributions. In the four component model, the two component distributions of the control mixture may be distinct from the two components of the case mixture distribution. In the two component unconstrained model, the components of the control and case mixtures are the same; however the mixture probabilities may differ for cases and controls. In the two component constrained model, all controls are distributed according to one of the two components while cases follow a mixture distribution of the two components. In the binormal model, cases and controls are distributed according to distinct unimodal distributions. These models assume that Box-Cox transformed case and control data with a common lambda parameter are distributed according to Gaussian mixture distributions. Model parameters are estimated using the expectation-maximization (EM) algorithm. Likelihood ratio test comparison of nested models can be performed using the lr.test function. AUC and PAUC values can be computed for the model-based and empirical ROC curves using the auc and pauc functions, respectively. The model-based and empirical ROC curves can be graphed using the roc.plot function. Finally, the model-based density estimates can be visualized by plotting a model object created with the bimixt.model function.
Depends: pROC
License: GPL (>= 3)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2015-08-24 18:18:50 UTC; mwinerip
Repository: CRAN
Date/Publication: 2015-08-25 00:54:26

● Data Source: CranContrib
● 0 images, 27 functions, 0 datasets
● Reverse Depends: 0

ThresholdROC : Threshold Estimation

Package: ThresholdROC
Type: Package
Title: Threshold Estimation
Version: 2.3
Date: 2015-12-13
Author: Sara Perez-Jaume, Natalia Pallares, Konstantina Skaltsa
Maintainer: Sara Perez-Jaume <spjaume@gmail.com>
Description: Point and interval estimations of optimum thresholds for continuous diagnostic tests (two- and three- state settings).
License: GPL (>= 2)
Depends: R (>= 3.1.0), MASS, numDeriv, pROC
NeedsCompilation: no
Packaged: 2015-12-13 19:22:01 UTC; Sara
Repository: CRAN
Date/Publication: 2015-12-14 08:57:02

● Data Source: CranContrib
● 0 images, 14 functions, 2 datasets
● Reverse Depends: 0