conda-forge / packages

Package Name Access Summary Updated
r-irkernel public The R kernel for the 'Jupyter' environment executes R code which the front-end ('Jupyter Notebook' or other front-ends) submits to the kernel via the network. 2019-07-18
pseudonetcdf public PseudoNetCDF like NetCDF except for many scientific format backends 2019-07-18
libv8 public V8 is Google’s open source high-performance JavaScript and WebAssembly engine, written in C++. 2019-07-18
r-nmf public Provides a framework to perform Non-negative Matrix Factorization (NMF). The package implements a set of already published algorithms and seeding methods, and provides a framework to test, develop and plug new/custom algorithms. Most of the built-in algorithms have been optimized in C++, and the main interface function provides an easy way of performing parallel computations on multicore machines. 2019-07-18
r-rstan public User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives. 2019-07-18
r-tidyr public An evolution of 'reshape2'. It's designed specifically for data tidying (not general reshaping or aggregating) and works well with 'dplyr' data pipelines. 2019-07-18
r-ggrepel public Provides text and label geoms for 'ggplot2' that help to avoid overlapping text labels. Labels repel away from each other and away from the data points. 2019-07-18
r-crosstalk public No Summary 2019-07-18
r-ggsignif public Enrich your 'ggplots' with group-wise comparisons. This package provides an easy way to indicate if two groups are significantly different. Commonly this is shown by a bracket on top connecting the groups of interest which itself is annotated with the level of significance (NS, *, **, ***). The package provides a single layer (geom_signif()) that takes the groups for comparison and the test (t.test(), wilcox.text() etc.) as arguments and adds the annotation to the plot. 2019-07-18
r-ggridges public Ridgeline plots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in 'ggplot2'. 2019-07-18
r-colourpicker public A colour picker that can be used as an input in Shiny apps or Rmarkdown documents. The colour picker supports alpha opacity, custom colour palettes, and many more options. A Plot Colour Helper tool is available as an RStudio Addin, which helps you pick colours to use in your plots. A more generic Colour Picker RStudio Addin is also provided to let you select colours to use in your R code. 2019-07-18
r-ggally public The R package 'ggplot2' is a plotting system based on the grammar of graphics. 'GGally' extends 'ggplot2' by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks. 2019-07-18
r-viridis public Port of the new matplotlib color maps ('viridis' - the default -, 'magma', 'plasma' and 'inferno') to R. matplotlib is a popular plotting library for python. These color maps are designed in such a way that they will analytically be perfectly perceptually-uniform, both in regular form and also when converted to black-and-white. They are also designed to be perceived by readers with the most common form of color blindness. 2019-07-18
r-cowplot public Some helpful extensions and modifications to the 'ggplot2' package. In particular, this package makes it easy to combine multiple 'ggplot2' plots into one and label them with letters, e.g. A, B, C, etc., as is often required for scientific publications. The package also provides a streamlined and clean theme that is used in the Wilke lab, hence the package name, which stands for Claus O. Wilke's plot package. 2019-07-18
r-ggsci public A collection of 'ggplot2' color palettes inspired by plots in scientific journals, data visualization libraries, science fiction movies, and TV shows. 2019-07-18
r-tidytext public Text mining for word processing and sentiment analysis using 'dplyr', 'ggplot2', and other tidy tools. 2019-07-18
tktable public Tktable is a 2D editable table widget 2019-07-18
r-dbplyr public A 'dplyr' back end for databases that allows you to work with remote database tables as if they are in-memory data frames. Basic features works with any database that has a 'DBI' back end; more advanced features require 'SQL' translation to be provided by the package author. 2019-07-18
r-fpc public Various methods for clustering and cluster validation. Fixed point clustering. Linear regression clustering. Clustering by merging Gaussian mixture components. Symmetric and asymmetric discriminant projections for visualisation of the separation of groupings. Cluster validation statistics for distance based clustering including corrected Rand index. Standardisation of cluster validation statistics by random clusterings and comparison between many clustering methods and numbers of clusters based on this. Cluster-wise cluster stability assessment. Methods for estimation of the number of clusters: Calinski-Harabasz, Tibshirani and Walther's prediction strength, Fang and Wang's bootstrap stability. Gaussian/multinomial mixture fitting for mixed continuous/categorical variables. Variable-wise statistics for cluster interpretation. DBSCAN clustering. Interface functions for many clustering methods implemented in R, including estimating the number of clusters with kmeans, pam and clara. Modality diagnosis for Gaussian mixtures. For an overview see package?fpc. 2019-07-18
r-rnetcdf public An interface to the NetCDF file format designed by Unidata for efficient storage of array-oriented scientific data and descriptions. The R interface is closely based on the C API of the NetCDF library, and it includes calendar conversions from the Unidata UDUNITS library. The current implementation supports all operations on NetCDF datasets in classic and 64-bit offset file formats, and NetCDF4-classic format is supported for reading and modification of existing files. 2019-07-18
ipyvuetify public Jupyter widgets based on vuetify UI components 2019-07-18
r-nomclust public Package for hierarchical clustering of objects characterized by nominal variables. 2019-07-18
r-dummies public Expands factors, characters and other eligible classes into dummy/indicator variables. 2019-07-18
r-fastdummies public Creates dummy columns from columns that have categorical variables (character or factor types). You can also specify which columns to make dummies out of, or which columns to ignore. Also creates dummy rows from character, factor, and Date columns. This package provides a significant speed increase from creating dummy variables through model.matrix(). 2019-07-18
py-pandoc-crossref public Installs pandoc-crossref conda package in pip and conda. 2019-07-18
r-statmod public A collection of algorithms and functions to aid statistical modeling. Includes growth curve comparisons, limiting dilution analysis (aka ELDA), mixed linear models, heteroscedastic regression, inverse-Gaussian probability calculations, Gauss quadrature and a secure convergence algorithm for nonlinear models. Includes advanced generalized linear model functions that implement secure convergence, dispersion modeling and Tweedie power-law families. 2019-07-18
r-tensora public Provides convenience functions for advanced linear algebra with tensors and computation with datasets of tensors on a higher level abstraction. It includes Einstein and Riemann summing conventions, dragging, co- and contravariate indices, parallel computations on sequences of tensors. 2019-07-18
r-spatstat public Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. Contains over 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots. 2019-07-18
r-timereg public Programs for Martinussen and Scheike (2006), `Dynamic Regression Models for Survival Data', Springer Verlag. Plus more recent developments. Additive survival model, semiparametric proportional odds model, fast cumulative residuals, excess risk models and more. Flexible competing risks regression including GOF-tests. Two-stage frailty modelling. PLS for the additive risk model. Lasso in the 'ahaz' package. 2019-07-18
r-rnifti public Provides very fast read and write access to images stored in the NIfTI-1 and ANALYZE-7.5 formats, with seamless synchronisation between compiled C and interpreted R code. Also provides a C/C++ API that can be used by other packages. Not to be confused with 'RNiftyReg', which performs image registration. 2019-07-18
r-rann public Finds the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library (v1.1.3). There is support for approximate as well as exact searches, fixed radius searches and 'bd' as well as 'kd' trees. The distance is computed using the L2 (Euclidean) metric. Please see package 'RANN.L1' for the same functionality using the L1 (Manhattan, taxicab) metric. 2019-07-18
r-sysfonts public Loading system fonts and Google Fonts <https://fonts.google.com/> into R, in order to support other packages such as 'R2SWF' and 'showtext'. 2019-07-18
r-rpf public The purpose of this package is to factor out logic and math common to Item Factor Analysis fitting, diagnostics, and analysis. It is envisioned as core support code suitable for more specialized IRT packages to build upon. Complete access to optimized C functions are made available with R_RegisterCCallable(). 2019-07-18
r-relimp public Functions to facilitate inference on the relative importance of predictors in a linear or generalized linear model, and a couple of useful Tcl/Tk widgets. 2019-07-18
r-rapportools public Helper functions that act as wrappers to more advanced statistical methods with the advantage of having sane defaults for quick reporting. 2019-07-18
r-rpmg public Really Poor Man's Graphical User Interface, used to create interactive R analysis sessions with simple R commands. 2019-07-18
r-svunit public A complete unit test system and functions to implement its GUI part. 2019-07-18
r-stabledist public No Summary 2019-07-18
r-reprex public Convenience wrapper that uses the 'rmarkdown' package to render small snippets of code to target formats that include both code and output. The goal is to encourage the sharing of small, reproducible, and runnable examples on code-oriented websites, such as <https://stackoverflow.com> and <https://github.com>, or in email. The user's clipboard is the default source of input code and the default target for rendered output. 'reprex' also extracts clean, runnable R code from various common formats, such as copy/paste from an R session. 2019-07-18
r-sparsebnutils public A set of tools for representing and estimating sparse Bayesian networks from continuous and discrete data, as described in Aragam, Gu, and Zhou (2017) <arXiv:1703.04025>. 2019-07-18
pandoc-crossref public Pandoc filter for cross-references 2019-07-18
r-wavethresh public Performs 1, 2 and 3D real and complex-valued wavelet transforms, nondecimated transforms, wavelet packet transforms, nondecimated wavelet packet transforms, multiple wavelet transforms, complex-valued wavelet transforms, wavelet shrinkage for various kinds of data, locally stationary wavelet time series, nonstationary multiscale transfer function modeling, density estimation. 2019-07-18
r-jomo public Similarly to Schafer's package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation (Carpenter and Kenward, 2013) <doi: 10.1002/9781119942283>. Novel aspects of 'jomo' are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model. 2019-07-18
r-entropy public This package implements various estimators of entropy, such as the shrinkage estimator by Hausser and Strimmer, the maximum likelihood and the Millow-Madow estimator, various Bayesian estimators, and the Chao-Shen estimator. It also offers an R interface to the NSB estimator. Furthermore, it provides functions for estimating Kullback-Leibler divergence, chi-squared, mutual information, and chi-squared statistic of independence. In addition there are functions for discretizing continuous random variables. 2019-07-18
r-exactranktests public Computes exact conditional p-values and quantiles using an implementation of the Shift-Algorithm by Streitberg & Roehmel. 2019-07-18
r-flashclust public Fast implementation of hierarchical clustering 2019-07-18
r-fracdiff public No Summary 2019-07-18
r-ks public Kernel smoothers for univariate and multivariate data, including densities, density derivatives, cumulative distributions, clustering, classification, density ridges, significant modal regions, and two-sample hypothesis tests. Chacon & Duong (2018) <doi:10.1201/9780429485572>. 2019-07-18
r-wikipedir public A wrapper for the MediaWiki API, aimed particularly at the Wikimedia 'production' wikis, such as Wikipedia. It can be used to retrieve page text, information about users or the history of pages, and elements of the category tree. 2019-07-18
r-gmodels public Various R programming tools for model fitting. 2019-07-18
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