Title: ML Estimator for Baseline-Placebo-Treatment (Three-group)
Author: Holger L. Kern <holger.kern@yale.edu>
Maintainer: Holger L. Kern <holger.kern@yale.edu>
Description: This package implements the Maximum Likelihood estimator
for three-group designs proposed by Gerber, Green, Kaplan, and

Title: ML Estimator for Baseline-Placebo-Treatment (Three-Group)
Maintainer: Holger L. Kern <hkern@fsu.edu>
Description: Implements the Maximum Likelihood estimator for baseline, placebo, and treatment groups (three-group) experiments with non-compliance proposed by Gerber, Green, Kaplan, and Kern (2010).
Packaged: 2015-09-09 17:38:55 UTC; holgerkern

Author: Maria Antonietta Del Ferraro, Henk A.L. Kiers, Paolo Giordani
Description: Component analysis for three-way data arrays by means of
Candecomp/Parafac, Tucker3, Tucker2 and Tucker1 models

Depends: R(>= 2.8.1), base, graphics, stats

Description: Component analysis for three-way data arrays by means of Candecomp/Parafac, Tucker3, Tucker2 and Tucker1 models

Description: Component analysis for three-way data arrays by means of Candecomp/Parafac, Tucker3, Tucker2 and Tucker1 models.
Depends: R(>= 2.8.1), base, stats, graphics, grDevices

Title: The Japanese Pictorial Maxim "See No Evil, Hear No Evil, Speak
Description: Does nothing useful, but perhaps does that nothing in an entertaining or informative fashion.

Title: Threshing and Reaping for Principal Components
Description: Defines the classes used to identify
outliers (threshing) and compute the number of significant principal
components and number of clusters (reaping) in a joint application
of PCA and hierarchical clustering. See Wang et al., 2018,
Depends: R (>= 3.1), ClassDiscovery, PCDimension
Imports: methods, stats, graphics, grDevices, MASS, colorspace, movMF,

Packaged: 2019-05-06 18:00:43 UTC; Kevin Coombes

Title: Optimum threshold estimation based on cost function in a two and
Description: The ThresholdROC package provides point and interval estimations of the optimum threshold for continuous diagnostic tests (two and three states setting). The point estimation is based on the definition of a cost function which we opt to minimise. An analytical estimator exists for the binormal and trinormal model and the empirical one is used for all settings. The interval estimation is based on the Delta method variance estimator in a binormal parametric setting and on methods on non-linear equations for the trinormal setting. Bootstrap methods are also provided for the confidence intervals.