About Anaconda Help Download Anaconda

mro_test / packages

Package Name Access Summary Updated
r-mgcv public Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar. Includes a gam() function, a wide variety of smoothers, JAGS support and distributions beyond the exponential family. 2023-06-16
r-survival public Contains the core survival analysis routines, including definition of Surv objects, Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models, and parametric accelerated failure time models. 2023-06-16
r-lattice public A powerful and elegant high-level data visualization system inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs, and is also flexible enough to handle most nonstandard requirements. See ?Lattice for an introduction. 2023-06-16
r-foreach public Support for the foreach looping construct. Foreach is an idiom that allows for iterating over elements in a collection, without the use of an explicit loop counter. This package in particular is intended to be used for its return value, rather than for its side effects. In that sense, it is similar to the standard lapply function, but doesn't require the evaluation of a function. Using foreach without side effects also facilitates executing the loop in parallel. 2023-06-16
mro-basics public No Summary 2023-06-16
mro-base public No Summary 2023-06-16
r-runit public R functions implementing a standard Unit Testing framework, with additional code inspection and report generation tools 2023-06-16
r-deployrrserve public Rserve acts as a socket server (TCP/IP or local sockets) which allows binary requests to be sent to R. Every connection has a separate workspace and working directory. Client-side implementations are available for popular languages such as C/C++ and Java, allowing any application to use facilities of R without the need of linking to R code. Rserve supports remote connection, user authentication and file transfer. A simple R client is included in this package as well. 2023-06-16
r-revomods public Microsoft modifications and extensions to standard R functions 2023-06-16
r-jsonlite public A fast JSON parser and generator optimized for statistical data and the web. Started out as a fork of 'RJSONIO', but has been completely rewritten in recent versions. The package offers flexible, robust, high performance tools for working with JSON in R and is particularly powerful for building pipelines and interacting with a web API. The implementation is based on the mapping described in the vignette (Ooms, 2014). In addition to converting JSON data from/to R objects, 'jsonlite' contains functions to stream, validate, and prettify JSON data. The unit tests included with the package verify that all edge cases are encoded and decoded consistently for use with dynamic data in systems and applications. 2023-06-16
r-cluster public Methods for Cluster analysis. Much extended the original from Peter Rousseeuw, Anja Struyf and Mia Hubert, based on Kaufman and Rousseeuw (1990) "Finding Groups in Data". 2023-06-16
r-codetools public Code analysis tools for R. 2023-06-16
r-png public This package provides an easy and simple way to read, write and display bitmap images stored in the PNG format. It can read and write both files and in-memory raw vectors. 2023-06-16
r-spatial public Functions for kriging and point pattern analysis. 2023-06-16
r-revoutilsmath public Utility functions for managing math threading. 2023-06-16
r-class public Various functions for classification, including k-nearest neighbour, Learning Vector Quantization and Self-Organizing Maps. 2023-06-16
r-kernsmooth public Functions for kernel smoothing (and density estimation) corresponding to the book: Wand, M.P. and Jones, M.C. (1995) "Kernel Smoothing". 2023-06-16
r-nnet public Software for feed-forward neural networks with a single hidden layer, and for multinomial log-linear models. 2023-06-16
r-revoioq public Test suite for Microsoft R Services. 2023-06-16
r-boot public Functions and datasets for bootstrapping from the book "Bootstrap Methods and Their Application" by A. C. Davison and D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S. 2023-06-16
r-checkpoint public The goal of checkpoint is to solve the problem of package reproducibility in R. Specifically, checkpoint allows you to install packages as they existed on CRAN on a specific snapshot date as if you had a CRAN time machine. To achieve reproducibility, the checkpoint() function installs the packages required or called by your project and scripts to a local library exactly as they existed at the specified point in time. Only those packages are available to your project, thereby avoiding any package updates that came later and may have altered your results. In this way, anyone using checkpoint's checkpoint() can ensure the reproducibility of your scripts or projects at any time. To create the snapshot archives, once a day (at midnight UTC) Microsoft refreshes the Austria CRAN mirror on the "Microsoft R Archived Network" server (<https://mran.microsoft.com/>). Immediately after completion of the rsync mirror process, the process takes a snapshot, thus creating the archive. Snapshot archives exist starting from 2014-09-17. 2023-06-16
r-revoutils public Utility functions for Microsoft R 2023-06-16
r-rodbc public No Summary 2023-06-16

© 2024 Anaconda, Inc. All Rights Reserved. (v4.0.2) Legal | Privacy Policy