# R team

#### 7 packages on CRAN

This package contains a proposed revision to the stats::ks.test() function and the associated ks.test.Rd help page. With one minor exception, it does not change the existing behavior of ks.test(), and it adds features necessary for doing one-sample tests with hypothesized discrete distributions. The package also contains cvm.test(), for doing one-sample Cramer-von Mises goodness-of-fit tests.

This package provides user-level functions to manage namespaces not (yet) available in base R: 'registerNamespace', 'unregisterNamespace', 'makeNamespace', and 'getRegisteredNamespace' ('makeNamespaces' is extracted from the R 'base' package source code: src/library/base/R/namespace.R)

Methods for the inference on and the simulation of Gaussian fields are provided, as well as methods for the simulation of extreme value random fields.

A collection of functions for data manipulation, plotting and statistical computing, to use separately or with the book "Visual Statistics. Use R!": Shipunov (2019) <http://ashipunov.info/shipunov/software/r/r-en.htm>. Most useful functions are probably Bclust(), Jclust() and BootA() which bootstrap hierarchical clustering; Recode...() which multiple recode in a fast, flexible and simple way; Misclass() which outputs confusion matrix even if classes are not concerted; Overlap() which calculates overlaps of convex hulls from any projection; and Pleiad() which is fast and flexible correlogram. In fact, there are much more useful functions, please see documentation.

Formally defined methods and classes for R objects, plus other programming tools, as described in the reference.

Support for parallel computation, including by forking (taken from package multicore), by sockets (taken from package snow) and random-number generation.

Public attention is an interesting field of study. The internet not only allows to access information in no time on virtually any subject but via page access statistics gathered by website authors the subject of attention as well can be studied. For the omnipresent Wikipedia those access statistics are made available via 'http://stats.grok.se' a server providing the information as file dumps as well as as web API. This package provides an easy to use, consistent and traffic minimizing approach to make those data accessible within R.