Package Name | Access | Summary | Updated |
---|---|---|---|

r-jade | public | Cardoso's JADE algorithm as well as his functions for joint diagonalization are ported to R. Also several other blind source separation (BSS) methods, like AMUSE and SOBI, and some criteria for performance evaluation of BSS algorithms, are given. The package is described in Miettinen, Nordhausen and Taskinen (2017) <doi:10.18637/jss.v076.i02>. | 2019-07-20 |

r-iptools | public | A toolkit for manipulating, validating and testing 'IP' addresses and ranges, along with datasets relating to 'IP' addresses. Tools are also provided to map 'IPv4' blocks to country codes. While it primarily has support for the 'IPv4' address space, more extensive 'IPv6' support is intended. | 2019-07-20 |

r-isa2 | public | The ISA is a biclustering algorithm that finds modules in an input matrix. A module or bicluster is a block of the reordered input matrix. | 2019-07-20 |

s-tui | public | Stress Terminal UI stress test and monitoring tool | 2019-07-20 |

r-kerasformula | public | Adds a high-level interface for 'keras' neural nets. kms() fits neural net and accepts R formulas to aid data munging and hyperparameter selection. kms() can optionally accept a compiled keras_sequential_model() from 'keras'. kms() accepts a number of parameters (like loss and optimizer) and splits the data into (optionally sparse) test and training matrices. kms() facilitates setting advanced hyperparameters (e.g., regularization). kms() returns a single object with predictions, a confusion matrix, and function call details. | 2019-07-20 |

r-kknn | public | Weighted k-Nearest Neighbors for Classification, Regression and Clustering. | 2019-07-20 |

r-iotools | public | Basic I/O tools for streaming and data parsing. | 2019-07-20 |

r-jqr | public | Client for 'jq', a 'JSON' processor (<https://stedolan.github.io/jq/>), written in C. 'jq' allows the following with 'JSON' data: index into, parse, do calculations, cut up and filter, change key names and values, perform conditionals and comparisons, and more. | 2019-07-20 |

r-keyring | public | Platform independent 'API' to access the operating system's credential store. Currently supports: 'Keychain' on 'macOS', Credential Store on 'Windows', the Secret Service 'API' on 'Linux', and a simple, platform independent store implemented with environment variables. Additional storage back-ends can be added easily. | 2019-07-20 |

r-ineq | public | Inequality, concentration, and poverty measures. Lorenz curves (empirical and theoretical). | 2019-07-20 |

r-intamap | public | Provides classes and methods for automated spatial interpolation. | 2019-07-20 |

r-incadata | public | Handle data in formats used by cancer centers in Sweden, both from 'INCA' (<https://rcc.incanet.se>) and by the older register platform 'Rockan'. All variables are coerced to suitable classes based on their format. Dates (from various formats such as with missing month or day, with or without century prefix or with just a week number) are all recognized as dates and coerced to the ISO 8601 standard (Y-m-d). Boolean variables (internally stored either as 0/1 or "True"/"False"/blanks when exported) are coerced to logical. Variable names ending in '_Beskrivning' and '_Varde' will be character, and 'PERSNR' will be coerced (if possible) to a valid personal identification number 'pin' (by the 'sweidnumbr' package). The package also allow the user to interactively choose if a variable should be coerced into a potential format even though not all of its values might conform to the recognized pattern. It also contain a caching mechanism in order to temporarily store data sets with its newly decided formats in order to not rerun the identification process each time. The package also include a mechanism to aid the documentation process connected to projects build on data from 'INCA'. From version 0.7, some general help functions are also included, as previously found in the 'rccmisc' package. | 2019-07-20 |

r-jmv | public | A suite of common statistical methods such as descriptives, t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, and factor analysis. This package is also useable from the 'jamovi' statistical spreadsheet (see <https://www.jamovi.org> for more information). | 2019-07-20 |

r-intergraph | public | Functions implemented in this package allow to coerce (i.e. convert) network data between classes provided by other R packages. Currently supported classes are those defined in packages: network and igraph. | 2019-07-20 |

r-invariantcausalprediction | public | Confidence intervals for causal effects, using data collected in different experimental or environmental conditions. Hidden variables can be included in the model with a more experimental version. | 2019-07-20 |

r-inlinedocs | public | Generates Rd files from R source code with comments. The main features of the default syntax are that (1) docs are defined in comments near the relevant code, (2) function argument names are not repeated in comments, and (3) examples are defined in R code, not comments. It is also easy to define a new syntax. | 2019-07-20 |

r-ipflasso | public | The core of the package is cvr2.ipflasso(), an extension of glmnet to be used when the (large) set of available predictors is partitioned into several modalities which potentially differ with respect to their information content in terms of prediction. For example, in biomedical applications patient outcome such as survival time or response to therapy may have to be predicted based on, say, mRNA data, miRNA data, methylation data, CNV data, clinical data, etc. The clinical predictors are on average often much more important for outcome prediction than the mRNA data. The ipflasso method takes this problem into account by using different penalty parameters for predictors from different modalities. The ratio between the different penalty parameters can be chosen by cross-validation. | 2019-07-20 |

r-janitor | public | The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and isolate duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff. | 2019-07-20 |

r-ismev | public | Functions to support the computations carried out in `An Introduction to Statistical Modeling of Extreme Values' by Stuart Coles. The functions may be divided into the following groups; maxima/minima, order statistics, peaks over thresholds and point processes. | 2019-07-20 |

r-irr | public | Coefficients of Interrater Reliability and Agreement for quantitative, ordinal and nominal data: ICC, Finn-Coefficient, Robinson'A, Kendall's W, Cohen's Kappa, ... | 2019-07-20 |

r-kedd | public | Smoothing techniques and computing bandwidth selectors of the nth derivative of a probability density for one-dimensional data. | 2019-07-20 |

r-kimisc | public | A collection of useful functions not found anywhere else, mainly for programming: Pretty intervals, generalized lagged differences, checking containment in an interval, and an alternative interface to assign(). | 2019-07-20 |

r-knitcitations | public | Provides the ability to create dynamic citations in which the bibliographic information is pulled from the web rather than having to be entered into a local database such as 'bibtex' ahead of time. The package is primarily aimed at authoring in the R 'markdown' format, and can provide outputs for web-based authoring such as linked text for inline citations. Cite using a 'DOI', URL, or 'bibtex' file key. See the package URL for details. | 2019-07-20 |

r-knitrbootstrap | public | A framework to create Bootstrap <http://getbootstrap.com/> HTML reports from 'knitr' 'rmarkdown'. | 2019-07-20 |

r-kpmt | public | Functions that implement the known population median test. | 2019-07-20 |

r-kpeaks | public | The input argument k which is the number of clusters is needed to start all of the partitioning clustering algorithms. In unsupervised learning applications, an optimal value of this argument is widely determined by using the internal validity indexes. Since these indexes suggest a k value which is computed on the clustering results after several runs of a clustering algorithm they are computationally expensive. On the contrary, 'kpeaks' enables to estimate k before running any clustering algorithm. It is based on a simple novel technique using the descriptive statistics of peak counts of the features in a data set. | 2019-07-20 |

r-liblinear | public | A wrapper around the LIBLINEAR C/C++ library for machine learning. | 2019-07-20 |

r-kriging | public | Simple and highly optimized ordinary kriging algorithm to plot geographical data | 2019-07-20 |

r-lokern | public | Kernel regression smoothing with adaptive local or global plug-in bandwidth selection. | 2019-07-20 |

gdal | public | GDAL is a translator library for raster and vector geospatial data formats that is released under an X/MIT style Open Source license by the Open Source Geospatial Foundation. | 2019-07-20 |

libgdal | public | The Geospatial Data Abstraction Library (GDAL) | 2019-07-20 |

r-landscapemetrics | public | Calculates landscape metrics for categorical landscape patterns in a tidy workflow. 'landscapemetrics' reimplements the most common metrics from 'FRAGSTATS' (<https://www.umass.edu/landeco/research/fragstats/fragstats.html>) and new ones from the current literature on landscape metrics. This package supports 'raster' spatial objects and takes RasterLayer, RasterStacks, RasterBricks or lists of RasterLayer from the 'raster' package as input arguments. It further provides utility functions to visualize patches, select metrics and building blocks to develop new metrics. | 2019-07-20 |

r-lime | public | When building complex models, it is often difficult to explain why the model should be trusted. While global measures such as accuracy are useful, they cannot be used for explaining why a model made a specific prediction. 'lime' (a port of the 'lime' 'Python' package) is a method for explaining the outcome of black box models by fitting a local model around the point in question an perturbations of this point. The approach is described in more detail in the article by Ribeiro et al. (2016) <arXiv:1602.04938>. | 2019-07-20 |

r-labdsv | public | A variety of ordination and community analyses useful in analysis of data sets in community ecology. Includes many of the common ordination methods, with graphical routines to facilitate their interpretation, as well as several novel analyses. | 2019-07-20 |

r-lhs | public | Provides a number of methods for creating and augmenting Latin Hypercube Samples. | 2019-07-20 |

r-logistf | public | Fit a logistic regression model using Firth's bias reduction method, equivalent to penalization of the log-likelihood by the Jeffreys prior. Confidence intervals for regression coefficients can be computed by penalized profile likelihood. Firth's method was proposed as ideal solution to the problem of separation in logistic regression. If needed, the bias reduction can be turned off such that ordinary maximum likelihood logistic regression is obtained. | 2019-07-20 |

r-lasso2 | public | Routines and documentation for solving regression problems while imposing an L1 constraint on the estimates, based on the algorithm of Osborne et al. (1998). | 2019-07-20 |

r-loe | public | Local Ordinal embedding (LOE) is one of graph embedding methods for unweighted graphs. | 2019-07-20 |

r-linkcomm | public | Link communities reveal the nested and overlapping structure in networks, and uncover the key nodes that form connections to multiple communities. linkcomm provides a set of tools for generating, visualizing, and analysing link communities in networks of arbitrary size and type. The linkcomm package also includes tools for generating, visualizing, and analysing Overlapping Cluster Generator (OCG) communities. | 2019-07-20 |

r-lobstr | public | A set of tools for inspecting and understanding R data structures inspired by str(). Includes ast() for visualizing abstract syntax trees, ref() for showing shared references, cst() for showing call stack trees, and obj_size() for computing object sizes. | 2019-07-20 |

r-log4r | public | The log4r package is meant to provide a fast, lightweight, object-oriented approach to logging in R based on the widely-emulated 'log4j' system and etymology. | 2019-07-20 |

r-logicreg | public | Routines for fitting Logic Regression models. Logic Regression is described in Ruczinski, Kooperberg, and LeBlanc (2003) <DOI:10.1198/1061860032238>. Monte Carlo Logic Regression is described in and Kooperberg and Ruczinski (2005) <DOI:10.1002/gepi.20042>. | 2019-07-20 |

r-logspline | public | Contains routines for logspline density estimation. The function oldlogspline() uses the same algorithm as the logspline package version 1.0.x; i.e. the Kooperberg and Stone (1992) algorithm (with an improved interface). The recommended routine logspline() uses an algorithm from Stone et al (1997) <DOI:10.1214/aos/1031594728>. | 2019-07-20 |

r-lpsolveapi | public | The lpSolveAPI package provides an R interface to 'lp_solve', a Mixed Integer Linear Programming (MILP) solver with support for pure linear, (mixed) integer/binary, semi-continuous and special ordered sets (SOS) models. | 2019-07-20 |

r-lahman | public | Provides the tables from the 'Sean Lahman Baseball Database' as a set of R data.frames. It uses the data on pitching, hitting and fielding performance and other tables from 1871 through 2018, as recorded in the 2019 version of the database. Documentation examples show how many baseball questions can be investigated. | 2019-07-20 |

r-lassopv | public | Estimate the p-values for predictors x against target variable y in lasso regression, using the regularization strength when each predictor enters the active set of regularization path for the first time as the statistic. This is based on the assumption that predictors (of the same variance) that (first) become active earlier tend to be more significant. Three null distributions are supported: normal and spherical, which are computed separately for each predictor and analytically under approximation, which aims at efficiency and accuracy for small p-values. | 2019-07-20 |

r-lemon | public | Functions for working with legends and axis lines of 'ggplot2', facets that repeat axis lines on all panels, and some 'knitr' extensions. | 2019-07-20 |

r-lim | public | Functions that read and solve linear inverse problems (food web problems, linear programming problems). These problems find solutions to linear or quadratic functions: min or max (f(x)), where f(x) = ||Ax-b||^2 or f(x) = sum(ai*xi) subject to equality constraints Ex=f and inequality constraints Gx>=h. Uses package limSolve. | 2019-07-20 |

r-liftr | public | Persistent reproducible reporting by containerization of R Markdown documents. | 2019-07-20 |

r-lle | public | LLE is a non-linear algorithm for mapping high-dimensional data into a lower dimensional (intrinsic) space. This package provides the main functions to performs the LLE alogrithm including some enhancements like subset selection, calculation of the intrinsic dimension etc. | 2019-07-20 |

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