R (>= 2.9.1), splines, quadprog, graphics, Rglpk, Benchmarking
A variety of functions for the best known and most innovative approaches to nonparametric boundary estimation. The selected methods are concerned with empirical, smoothed, unrestricted as well as constrained fits under both separate and multiple shape constraints. They cover robust approaches to outliers  as well as data envelopment techniques based on piecewise polynomials, splines, local linear fitting, extreme values and kernel smoothing. The package also seamlessly allows for Monte Carlo comparisons among these different estimation methods.  Its use is illustrated via a number of empirical applications and simulated examples.

Benchmarking, np, quadprog, Rglpk, splines

Benchmarking, np, quadprog, Rglpk (>= 0.6-2), splines

Non Parametric Test for Detecting Changes in the Copula
A non parametric test for change points detection in the dependence between the components of multivariate data, with or without (multiple) changes in the marginal distributions.

A non parametric test for change points detection in the dependence between the components of multivariate data, with or without (multiple) changes in the marginal distributions. The full details, justification and examples are published in Rohmer (2016) <doi:10.1016/j.spl.2016.06.026>.

Some nonparametric tests for change-point detection in
(multivariate) observations
Provides nonparametric tests for assessing whether possibly serially dependent (multivariate) continuous observations have the same c.d.f. or not. In addition to tests focusing directly on the (multivariate) c.d.f., the package contains tests designed to be particularly sensitive to changes in the underlying copula.

Provides nonparametric tests for assessing whether possibly serially dependent (multivariate) observations have the same c.d.f. or not. In addition to tests focusing directly on the (multivariate) c.d.f., the package contains tests designed to be particularly sensitive to changes in the underlying copula, Spearman's rho or certain quantities that can be estimated using one-sample U-statistics of order two such as the variance, Gini's mean difference or Kendall's tau.