Description: A non-parametric framework based on  estimation statistics principle. Its main purpose is to  infer orders of empirical distributions from different categories based on a probability of finding a value in one distribution that is greater than an expectation of another distribution. Given a set of ordered-pair of real-category values the framework is capable of 1) inferring orders of  domination  of  categories  and  representing  orders  in  the form of a graph; 2) estimating  magnitude  of  difference  between  a  pair  of categories in forms of mean-difference confidence intervals; and 3) visualizing  domination  orders  and  magnitudes  of  difference of categories. The publication of this package is at Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, and Suttipong Thajchayapong (2020) <doi:10.1016/j.heliyon.2020.e05435>.

Title: Euclidean Distance-Optimized Data Transformation
Author: Jorn Lotsch[aut,cre], Alfred Ultsch[aut]
Description: A data transformation method which takes into account the special property of scale non-invariance with a breakpoint at 1 of the Euclidean distance.
Imports: ABCanalysis, AdaptGauss, DistributionOptimization, ClusterR,
DataVisualizations, ggplot2, grDevices, methods, stats, rlang

Imports: methods, stats, utils, ABCanalysis, opGMMassessment

Title: Estimation of the effective dimension reduction (EDR) space
Description: The library contains R-functions to estimate the
effective dimension reduction space in multi-index regression models.
Copyright: This library is Copyright (C) 2006-2007 Weierstrass Institute for
Note: This software comes with NO warranty!
Packaged: Tue Nov 20 13:36:46 2007; polzehl

Description: The library contains R-functions to estimate the effective
dimension reduction space in multi-index regression models.

Copyright: This library is Copyright (C) 2006-2010 Weierstrass
Institute for Applied Analysis and Stochastics.

Copyright: This library is Copyright (C) 2006-2013 Weierstrass

Description: The package contains R-functions to estimate the effective