conda-forge / packages

Package Name Access Summary Updated
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' (<>) 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-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
r-logging public logging is a pure R package that implements the ubiquitous log4j package. 2019-07-20
boost-cpp public Free peer-reviewed portable C++ source libraries. 2019-07-20
r-markovchain public Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided. 2019-07-20
r-maldiquant public A complete analysis pipeline for matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass spectrometry data. In addition to commonly used plotting and processing methods it includes distinctive features, namely baseline subtraction methods such as morphological filters (TopHat) or the statistics-sensitive non-linear iterative peak-clipping algorithm (SNIP), peak alignment using warping functions, handling of replicated measurements as well as allowing spectra with different resolutions. 2019-07-20
r-matching public Provides functions for multivariate and propensity score matching and for finding optimal balance based on a genetic search algorithm. A variety of univariate and multivariate metrics to determine if balance has been obtained are also provided. 2019-07-20
r-maptpx public Posterior maximization for topic models (LDA) in text analysis, as described in Taddy (2012) `on estimation and selection for topic models'. Previous versions of this code were included as part of the textir package. If you want to take advantage of openmp parallelization, uncomment the relevant flags in src/MAKEVARS before compiling. 2019-07-20
r-memuse public How much ram do you need to store a 100,000 by 100,000 matrix? How much ram is your current R session using? How much ram do you even have? Learn the scintillating answer to these and many more such questions with the 'memuse' package. 2019-07-20
r-mcmcglmm public MCMC Generalised Linear Mixed Models. 2019-07-20
r-metarnaseq public Implementation of two p-value combination techniques (inverse normal and Fisher methods). A vignette is provided to explain how to perform a meta-analysis from two independent RNA-seq experiments. 2019-07-20
r-metr public Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences. 2019-07-20
r-lsr public A collection of tools intended to make introductory statistics easier to teach, including wrappers for common hypothesis tests and basic data manipulation. It accompanies Navarro, D. J. (2015). Learning Statistics with R: A Tutorial for Psychology Students and Other Beginners, Version 0.5. [Lecture notes] School of Psychology, University of Adelaide, Adelaide, Australia. ISBN: 978-1-326-18972-3. URL: 2019-07-20
r-meta public User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - fixed effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - statistical tests and trim-and-fill method to evaluate bias in meta-analysis; - import data from 'RevMan 5'; - prediction interval, Hartung-Knapp and Paule-Mandel method for random effects model; - cumulative meta-analysis and leave-one-out meta-analysis; - meta-regression; - generalised linear mixed models; - produce forest plot summarising several (subgroup) meta-analyses. 2019-07-20
r-metap public The canonical way to perform meta-analysis involves using effect sizes. When they are not available this package provides a number of methods for meta-analysis of significance values including the methods of Edgington, Fisher, Lancaster, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results; and a routine for graphical display. 2019-07-20
r-medicalrisk public Generates risk estimates and comorbidity flags from ICD-9-CM codes available in administrative medical datasets. The package supports the Charlson Comorbidity Index, the Elixhauser Comorbidity classification, the Revised Cardiac Risk Index, and the Risk Stratification Index. Methods are table-based, fast, and use the 'plyr' package, so parallelization is possible for large jobs. Also includes a sample of real ICD-9 data for 100 patients from a publicly available dataset. 2019-07-20
r-mcl public Contains the Markov cluster algorithm (MCL) for identifying clusters in networks and graphs. The algorithm simulates random walks on a (n x n) matrix as the adjacency matrix of a graph. It alternates an expansion step and an inflation step until an equilibrium state is reached. 2019-07-20
r-matrix.utils public Implements data manipulation methods such as cast, aggregate, and merge/join for Matrix and matrix-like objects. 2019-07-20
r-matrixeqtl public Matrix eQTL is designed for fast eQTL analysis on large datasets. Matrix eQTL can test for association between genotype and gene expression using linear regression with either additive or ANOVA genotype effects. The models can include covariates to account for factors as population stratification, gender, and clinical variables. It also supports models with heteroscedastic and/or correlated errors, false discovery rate estimation and separate treatment of local (cis) and distant (trans) eQTLs. 2019-07-20
r-mcbiopi public Computes the prime implicants or a minimal disjunctive normal form for a logic expression presented by a truth table or a logic tree. Has been particularly developed for logic expressions resulting from a logic regression analysis, i.e. logic expressions typically consisting of up to 16 literals, where the prime implicants are typically composed of a maximum of 4 or 5 literals. 2019-07-20
r-mefa public A framework package aimed to provide standardized computational environment for specialist work via object classes to represent the data coded by samples, taxa and segments (i.e. subpopulations, repeated measures). It supports easy processing of the data along with cross tabulation and relational data tables for samples and taxa. An object of class `mefa' is a project specific compendium of the data and can be easily used in further analyses. Methods are provided for extraction, aggregation, conversion, plotting, summary and reporting of `mefa' objects. Reports can be generated in plain text or LaTeX format. Vignette contains worked examples. 2019-07-20
r-margins public An R port of Stata's 'margins' command, which can be used to calculate marginal (or partial) effects from model objects. 2019-07-20
r-maptree public Functions with example data for graphing, pruning, and mapping models from hierarchical clustering, and classification and regression trees. 2019-07-20
r-magicaxis public Functions to make useful (and pretty) plots for scientific plotting. Additional plotting features are added for base plotting, with particular emphasis on making attractive log axis plots. 2019-07-20
r-mapplots public Create simple maps; add sub-plots like pie plots to a map or any other plot; format, plot and export gridded data. The package was developed for displaying fisheries data but most functions can be used for more generic data visualisation. 2019-07-20
r-lsd public Create lots of colorful plots in a plethora of variations. Try the LSD demotour(). 2019-07-20
r-lsa public The basic idea of latent semantic analysis (LSA) is, that text do have a higher order (=latent semantic) structure which, however, is obscured by word usage (e.g. through the use of synonyms or polysemy). By using conceptual indices that are derived statistically via a truncated singular value decomposition (a two-mode factor analysis) over a given document-term matrix, this variability problem can be overcome. 2019-07-20
r-mongolite public High-performance MongoDB client based on 'mongo-c-driver' and 'jsonlite'. Includes support for aggregation, indexing, map-reduce, streaming, encryption, enterprise authentication, and GridFS. The online user manual provides an overview of the available methods in the package: <>. 2019-07-20
r-mlr public Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized. 2019-07-20
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