Total number of libraries: 5
1) alphahull
Generalization of the convex hull of a sample of points in the plane. This package computes the alphashape and alphaconvex hull of a given sample of points in the plane. The concepts of alphashape and alphaconvex hull generalize the definition of the convex hull of a finite set of points. The programming is based on the duality between the Voronoi diagram and Delaunay triangulation. The package also includes a function that returns the Delaunay mesh of a given sample of points and its dual Voronoi diagram in one single object.
2) alphashape3d
Implementation of the 3D alphashape for the reconstruction of 3D sets from a point cloud The package alphashape3d presents the implementation in R of the alphashape of a finite set of points in the threedimensional space. This geometric structure generalizes the convex hull and allows to recover the shape of nonconvex and even nonconnected sets in 3D, given a random sample of points taken into it. Besides the computation of the alphashape, the package alphashape3d provides users with functions to compute the volume of the alphashape, identify the connected components and facilitate the threedimensional graphical visualization of the estimated set.
3) fda.usc
Functional Data Analysis and Utilities for Statistical Computing (fda.usc). The new R package fda.usc includes methods for:
1. Functional Data Representation 2. Exploratory Functional Data Analysis 3. Functional Outlier Detection 4. Functional Regression with Scalar Response 5. Functional Supervised and NonSupervised Classification 6. Functional ANOVA
The purpose of this package is to integrate own developments in Functional Data Analysis with those from other authors: fda package and/or group STAPH The package fda.usc is avalaible through CRAN and further documentation are available:
4) DTDA: Doubly truncated data analysis
This package implements different algorithms for analyzing randomly truncated data, onesided and twosided (i.e. doubly) truncated data. Two real data sets are included. It incorporates the iterative methods introduced by Efron and Petrosian (1999) and Shen (2008). Estimation of the lifetime distribution function and truncation times distributions is possible, together with the corresponding pointwise confidence limits based on bootstrap methods. Plots of cumulative distributions and survival functions are provided. Two real data sets are included: righttruncated AIDS data and doubly truncated data on quasar luminosities.
5) Package NPCirc: Nonparametric Circular Methods
This package implements nonparametric kernel methods for density and regression estimation for circular data. Specifically, a circular kernel density estimation procedure is provided, jointly with different alternatives for chosing the smoothing parameter. In the regression setting, nonparametric estimation for circularlinear, circularcircular and linearcircular data is also possible via the adaptation of the classical NadarayaWatson and local linear estimators. In order to assess the significance of the features observed in the smooth curves, both for density and regression with a circular covariate and a linear response, a SiZer technique is developed for circular data, namely CircSiZer. Some real data examples are also included in the package.
