Logiciels et Codes

Packages R maintenus

Laurent T. et al. (2012). GeoXp: Interactive exploratory spatial data analysis. R package version 1.6.2.
"GeoXp is a tool for researchers in spatial statistics, spatial econometrics, geography, ecology etc allowing to link dynamically statistical plots with elementary maps. This coupling consists in the fact that the selection of a zone on the map results in the automatic highlighting of the corresponding points on the statistical graph or reversely the selection of a portion of the graph results in the automatic highlighting of the corresponding points on the map. GeoXp includes tools from different areas of spatial statistics including geostatistics as well as spatial econometrics and point processes. Besides elementary plots like boxplots, histograms or simple scatterplot, GeoXp also couples with maps Moran scatterplots, variogram cloud, Lorentz Curves,...In order to make the most of the multidimensionality of the data, GeoXp includes some dimension reduction techniques such as PCA".

Aragon Y. et Laurent T. (2011). Séries temporelles avec R – Méthodes et cas. R package version 1.4.
"Functions, data sets and exercises solutions for the book 'Séries temporelles avec R - Méthodes et cas' (Yves Aragon, Springer, 2011). For all chapters, a vignette is available with some additional material and exercises solutions".

Daouia A. et Laurent T. (2012). frontiles: Partial Frontier Efficiency Analysis. R package version 1.2.
"It calculates the alpha-quantile and order-m efficiency score in multi-dimension and computes several summaries and representation of the associated frontiers in 2d and 3d".
Daouia A., Laurent T. et Noh H. (2013). npbr: Nonparametric Boundary Regression. R package version 1.0. "This package provides functions for the best known approaches to nonparametric boundary estimation. The selected methods are concerned with empirical, smooth, unconstrained as well as restricted estimates under both separate and multiple shape constraints. The package also allows for Monte Carlo comparisons among these different estimation procedures, illustrating the simulation experiments by Daouia, Noh and Park (2013), Data envelope fitting with constrained polynomial splines, TSE Working Paper, http://www.tse-fr.eu/images/doc/wp/etrie/wp_tse_449.pdf

Codes R illustrant des articles