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

r-essentials | public | Some essential packages for working with R | 2021-03-02 |

r-base | None | R is a free software environment for statistical computing and graphics. | 2020-05-20 |

r-pbdzmq | public | 'ZeroMQ' is a well-known library for high-performance asynchronous messaging in scalable, distributed applications. This package provides high level R wrapper functions to easily utilize 'ZeroMQ'. We mainly focus on interactive client/server programming frameworks. For convenience, a minimal 'ZeroMQ' library (4.2.2) is shipped with 'pbdZMQ', which can be used if no system installation of 'ZeroMQ' is available. A few wrapper functions compatible with 'rzmq' are also provided. | 2020-05-20 |

r | None | R is a free software environment for statistical computing and graphics. | 2020-05-06 |

r-nloptr | None | Solve optimization problems using an R interface to NLopt. NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. See <http://ab-initio.mit.edu/wiki/index.php/NLopt_Introduction> for more information on the available algorithms. During installation of nloptr on Unix-based systems, the installer checks whether the NLopt library is installed on the system. If the NLopt library cannot be found, the code is compiled using the NLopt source included in the nloptr package. | 2020-05-06 |

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). | 2020-04-03 |

r-langevin | public | Estimate drift and diffusion functions from time series and generate synthetic time series from given drift and diffusion coefficients. | 2020-04-03 |

r-largelist | public | Functions to write or append a R list to a file, as well as read, remove, modify elements from it without restoring the whole list. | 2020-04-03 |

r-landscaper | public | Simulates categorical maps on actual geographical realms, starting from either empty landscapes or landscapes provided by the user (e.g. land use maps). Allows to tweak or create landscapes while retaining a high degree of control on its features, without the hassle of specifying each location attribute. In this it differs from other tools which generate null or neutral landscapes in a theoretical space. The basic algorithm currently implemented uses a simple agent style/cellular automata growth model, with no rules (apart from areas of exclusion) and von Neumann neighbourhood (four cells, aka Rook case). Outputs are raster dataset exportable to any common GIS format. | 2020-04-03 |

r-laf | public | Methods for fast access to large ASCII files. Currently the following file formats are supported: comma separated format (CSV) and fixed width format. It is assumed that the files are too large to fit into memory, although the package can also be used to efficiently access files that do fit into memory. Methods are provided to access and process files blockwise. Furthermore, an opened file can be accessed as one would an ordinary data.frame. The LaF vignette gives an overview of the functionality provided. | 2020-04-03 |

r-l1pack | public | L1 estimation for linear regression, density, distribution function, quantile function and random number generation for univariate and multivariate Laplace distribution. | 2020-04-03 |

r-l0ara | public | An efficient procedure for feature selection for generalized linear models with L0 penalty, including linear, logistic, Poisson, gamma, inverse Gaussian regression. Adaptive ridge algorithms are used to fit the models. | 2020-04-03 |

r-kza | public | Time Series Analysis including break detection, spectral analysis, KZ Fourier Transforms. | 2020-04-03 |

r-kyotil | public | Helper functions for creating formatted summary of regression models, writing publication-ready tables to latex files, and running Monte Carlo experiments. | 2020-04-03 |

r-kvh | public | The format KVH is a lightweight format that can be read/written both by humans and machines. It can be useful in situations where XML or alike formats seem to be an overkill. We provide an ability to parse KVH files in R pretty fast due to 'Rcpp' use. | 2020-04-03 |

r-ksamples | public | Compares k samples using the Anderson-Darling test, Kruskal-Wallis type tests with different rank score criteria, Steel's multiple comparison test, and the Jonckheere-Terpstra (JT) test. It computes asymptotic, simulated or (limited) exact P-values, all valid under randomization, with or without ties, or conditionally under random sampling from populations, given the observed tie pattern. Except for Steel's test and the JT test it also combines these tests across several blocks of samples. Also analyzed are 2 x t contingency tables and their blocked combinations using the Kruskal-Wallis criterion. Steel's test is inverted to provide simultaneous confidence bounds for shift parameters. A plotting function compares tail probabilities obtained under asymptotic approximation with those obtained via simulation or exact calculations. | 2020-04-03 |

r-ksnn | public | Prediction with k* nearest neighbor algorithm based on a publication by Anava and Levy (2016) <arXiv:1701.07266>. | 2020-04-03 |

r-kriging | public | Simple and highly optimized ordinary kriging algorithm to plot geographical data | 2020-04-03 |

r-kodama | public | KODAMA algorithm is an unsupervised and semi-supervised learning algorithm that performs feature extraction from noisy and high-dimensional data. It facilitates identification of patterns representing underlying groups on all samples in a data set. The algorithm was published by Cacciatore et al. 2014 <DOI:10.1073/pnas.1220873111>. Addition functions was introduced by Cacciatore et al. 2017 <DOI:10.1093/bioinformatics/btw705> to facilitate the identification of key features associated with the generated output and are easily interpretable for the user. Cross-validated techniques are also included in this package. | 2020-04-03 |

r-konpsurv | public | The K-sample omnibus non-proportional hazards (KONP) tests are powerful non-parametric tests for comparing K (>=2) hazard functions based on right-censored data (Gorfine, Schlesinger and Hsu, 2019, <arXiv:1901.05739v1>). These tests are consistent against any differences between the hazard functions of the groups. The KONP tests are often more powerful than other existing tests, especially under non-proportional hazard functions. | 2020-04-03 |

r-kolmim | public | Provides an alternative, more efficient evaluation of extreme probabilities of Kolmogorov's goodness-of-fit measure, Dn, when compared to the original implementation of Wang, Marsaglia, and Tsang. These probabilities are used in Kolmogorov-Smirnov tests when comparing two samples. | 2020-04-03 |

r-knor | public | The k-means 'NUMA' Optimized Routine library or 'knor' is a highly optimized and fast library for computing k-means in parallel with accelerations for Non-Uniform Memory Access ('NUMA') architectures. | 2020-04-03 |

r-knncat | public | Scale categorical variables in such a way as to make NN classification as accurate as possible. The code also handles continuous variables and prior probabilities, and does intelligent variable selection and estimation of both error rates and the right number of NN's. | 2020-04-03 |

r-kknn | public | Weighted k-Nearest Neighbors for Classification, Regression and Clustering. | 2020-04-03 |

r-keyboardsimulator | public | Control your keyboard and mouse with R code by simulating key presses and mouse clicks. The input simulation is implemented with the Windows API. | 2020-04-03 |

r-kissmig | public | Simulating species migration and range dynamics under stable or changing environmental conditions based on a simple, raster-based, stochastic migration model. Providing accessibility for considering species migration in niche-based species distribution models. | 2020-04-03 |

r-kfksds | public | Naive implementation of the Kalman filter, smoother and disturbance smoother for state space models. | 2020-04-03 |

r-kfas | public | State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details. | 2020-04-03 |

r-keypress | public | Wait for a single key press at the 'R' prompt. This works in terminals, but does not currently work in the 'Windows' 'GUI', the 'OS X' 'GUI' ('R.app'), in 'Emacs' 'ESS', in an 'Emacs' shell buffer or in 'R Studio'. In these cases 'keypress' stops with an error message. | 2020-04-03 |

r-kexpmv | public | Implements functions from 'EXPOKIT' (<https://www.maths.uq.edu.au/expokit/>) to calculate matrix exponentials, Sidje RB, (1998) <doi:10.1145/285861.285868>. Includes functions for small dense matrices along with functions for large sparse matrices. The functions for large sparse matrices implement Krylov subspace methods which help minimise the computational complexity for matrix exponentials. 'Kexpmv' can be utilised to calculate both the matrix exponential in isolation along with the product of the matrix exponential and a vector. | 2020-04-03 |

r-kernelknn | public | Extends the simple k-nearest neighbors algorithm by incorporating numerous kernel functions and a variety of distance metrics. The package takes advantage of 'RcppArmadillo' to speed up the calculation of distances between observations. | 2020-04-03 |

r-kere | public | An efficient algorithm inspired by majorization-minimization principle for solving the entire solution path of a flexible nonparametric expectile regression estimator constructed in a reproducing kernel Hilbert space. | 2020-04-03 |

r-kerndwd | public | A novel implementation that solves the linear distance weighted discrimination and the kernel distance weighted discrimination. | 2020-04-03 |

r-kendall | public | Computes the Kendall rank correlation and Mann-Kendall trend test. See documentation for use of block bootstrap when there is autocorrelation. | 2020-04-03 |

r-kaps | public | This package provides some routines to conduct the K-adaptive parititioning (kaps) algorithm for survival data. A function kaps is an implementation version of our algorithm. | 2020-04-03 |

r-kappalab | public | S4 tool box for capacity (or non-additive measure, fuzzy measure) and integral manipulation in a finite setting. It contains routines for handling various types of set functions such as games or capacities. It can be used to compute several non-additive integrals: the Choquet integral, the Sugeno integral, and the symmetric and asymmetric Choquet integrals. An analysis of capacities in terms of decision behavior can be performed through the computation of various indices such as the Shapley value, the interaction index, the orness degree, etc. The well-known MÃ¶bius transform, as well as other equivalent representations of set functions can also be computed. Kappalab further contains seven capacity identification routines: three least squares based approaches, a method based on linear programming, a maximum entropy like method based on variance minimization, a minimum distance approach and an unsupervised approach based on parametric entropies. The functions contained in Kappalab can for instance be used in the framework of multicriteria decision making or cooperative game theory. | 2020-04-03 |

r-kamila | public | Implements methods for clustering mixed-type data, specifically combinations of continuous and nominal data. Special attention is paid to the often-overlooked problem of equitably balancing the contribution of the continuous and categorical variables. This package implements KAMILA clustering, a novel method for clustering mixed-type data in the spirit of k-means clustering. It does not require dummy coding of variables, and is efficient enough to scale to rather large data sets. Also implemented is Modha-Spangler clustering, which uses a brute-force strategy to maximize the cluster separation simultaneously in the continuous and categorical variables. For more information, see Foss, Markatou, Ray, & Heching (2016) <doi:10.1007/s10994-016-5575-7> and Foss & Markatou (2018) <doi:10.18637/jss.v083.i13>. | 2020-04-03 |

r-jwutil | public | This is a set of simple utilities for various data manipulation and testing tasks. The goal is to use core R tools well, without bringing in many dependencies. Main areas of interest are semi-automated data frame manipulation, such as converting factors in multiple binary indicator columns. There are testing functions which provide 'testthat' expectations to permute arguments to function calls. There are functions and data to test extreme numbers, dates, and bad input of various kinds which should allow testing failure and corner cases, which can be used for fuzzing your functions. The test suite has many examples of usage. | 2020-04-03 |

r-junctions | public | Individual based simulations of hybridizing populations, where the accumulation of junctions is tracked. Furthermore, mathematical equations are provided to verify simulation outcomes. Both simulations and mathematical equations are based on Janzen (2018) <doi:10.1101/058107>. | 2020-04-03 |

r-jumptest | public | A fast simulation on stochastic volatility model, with jump tests, p-values pooling, and FDR adjustments. | 2020-04-03 |

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. | 2020-04-03 |

r-juliacall | public | Provides an R interface to 'Julia', which is a high-level, high-performance dynamic programming language for numerical computing, see <https://julialang.org/> for more information. It provides a high-level interface as well as a low-level interface. Using the high level interface, you could call any 'Julia' function just like any R function with automatic type conversion. Using the low level interface, you could deal with C-level SEXP directly while enjoying the convenience of using a high-level programming language like 'Julia'. | 2020-04-03 |

r-jtgwas | public | The core of this 'Rcpp' based package is a function to compute standardized Jonckheere-Terpstra test statistics for large numbers of dependent and independent variables, e.g., genome-wide analysis. It implements 'OpenMP', allowing the option of computing on multiple threads. Supporting functions are also provided to calculate p-values and summarize results. | 2020-04-03 |

r-jrf | public | Simultaneous estimation of multiple related networks. | 2020-04-03 |

r-jousboost | public | Implements under/oversampling for probability estimation. To be used with machine learning methods such as AdaBoost, random forests, etc. | 2020-04-03 |

r-jmotif | public | Implements time series z-normalization, SAX, HOT-SAX, VSM, SAX-VSM, RePair, and RRA algorithms facilitating time series motif (i.e., recurrent pattern), discord (i.e., anomaly), and characteristic pattern discovery along with interpretable time series classification. | 2020-04-03 |

r-jointdiag | public | Different algorithms to perform approximate joint diagonalization of a finite set of square matrices. Depending on the algorithm, orthogonal or non-orthogonal diagonalizer is found. These algorithms are particularly useful in the context of blind source separation. | 2020-04-03 |

r-jmi | public | Computes the Jackknife Mutual Information (JMI) between two random vectors and provides the p-value for dependence tests. See Zeng, X., Xia, Y. and Tong, H. (2018) <doi:10.1073/pnas.1715593115>. | 2020-04-03 |

r-jmdl | public | Fit joint mean-correlation models for discrete longitudinal data (Tang CY,Zhang W, Leng C, 2017 <doi:10.5705/ss.202016.0435>). | 2020-04-03 |

r-jaspar | public | R modules for JASPAR data processing and visualization | 2020-04-03 |

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