Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.
API method:
GET /api/packages?search=hello&page=1&limit=20
where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned
in response headers.
If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.
This package converts between GeoJSON and Simple Feature objects.
Efficient C++ optimized functions for numerical and symbolic calculus. It includes basic symbolic arithmetic, tensor calculus, Einstein summing convention, fast computation of the Levi-Civita symbol and generalized Kronecker delta, Taylor series expansion, multivariate Hermite polynomials, accurate high-order derivatives, differential operators (Gradient, Jacobian, Hessian, Divergence, Curl, Laplacian) and numerical integration in arbitrary orthogonal coordinate systems: cartesian, polar, spherical, cylindrical, parabolic or user defined by custom scale factors.
This package implements a general framework for finite mixtures of regression models using the EM algorithm. FlexMix provides the E-step and all data handling, while the M-step can be supplied by the user to easily define new models. Existing drivers implement mixtures of standard linear models, generalized linear models and model-based clustering.
This package provides functions to work with date-times and time-spans: fast and user friendly parsing of date-time data, extraction and updating of components of a date-time (years, months, days, hours, minutes, and seconds), algebraic manipulation on date-time and time-span objects. The lubridate package has a consistent and memorable syntax that makes working with dates easy and fun.
This package provides various functions for classification, including k-nearest neighbour, Learning Vector Quantization and Self-Organizing Maps.
This package provides a dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets.
This package implements easy-to-use functions to generate 2-7 sets Venn plot in publication quality. ggVennDiagram plot Venn using well-defined geometry dataset and ggplot2. The shapes of 2-4 sets Venn use circles and ellipses, while the shapes of 4-7 sets Venn use irregular polygons (4 has both forms), which are developed and imported from another package venn. We provide internal functions to integrate shape data with user provided sets data, and calculated the geometry of every regions/intersections of them, then separately plot Venn in three components: set edges, set labels, and regions. From version 1.0, it is possible to customize these components as you demand in ordinary ggplot2 grammar.
This package provides an interface to a large number of classification and regression techniques. These techniques include machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Also included:
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.
Users may want to align plots with associated information that requires axes to be exactly matched in subplots, e.g. hierarchical clustering with a heatmap. This package provides utilities to align associated subplots to a main plot at different sides (left, right, top and bottom) with axes exactly matched.
This package provides functions to make zebra-striped tables (tables with alternating row colors) in LaTeX and HTML formats easily from data.frame, matrix, lm, aov, anova, glm, coxph, nls, fitdistr, mytable and cbind.mytable objects.
This package provides functions for computing the density and the distribution function of multivariate normal and "t" random variables, and for generating random vectors sampled from these distributions. Probabilities are computed via non-Monte Carlo methods.
This is a package to simplify loading of system fonts and Google Fonts into R, in order to support other packages.
This package provides a suite of functions to help ease the use of the d3.js visualization library in R. These helpers include htmltools::htmlDependency functions, hierarchy builders, and conversion tools for partykit, igraph, table, and data.frame R objects into the JSON format that the d3.js library expects.
This package helps you with creation and use of R repositories via helper functions to insert packages into a repository, and to add repository information to the current R session. Two primary types of repositories are supported: gh-pages at GitHub, as well as local repositories on either the same machine or a local network. Drat is a recursive acronym: Drat R Archive Template.
The r-nleqslv package solves a system of nonlinear equations using a Broyden or a Newton method with a choice of global strategies such as line search and trust region. There are options for using a numerical or user supplied Jacobian, for specifying a banded numerical Jacobian and for allowing a singular or ill-conditioned Jacobian.
This package provides an R interface to all Enrichr databases, a web-based tool for analyzing gene sets and returns any enrichment of common annotated biological functions.
This package lets you use syntax inspired by the package glue to extract matched substrings in a more intuitive and compact way than by using standard regular expressions.
This package provides a statistical method to impute the missing values in accelerometer data. The methodology includes both parametric and semi-parametric multiple imputations under the zero-inflated Poisson lognormal model. It also provides multiple functions to preprocess the accelerometer data previous to the missing data imputation. These include detecting the wearing and the non-wearing time, selecting valid days and subjects, and creating plots.
This package provides tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). The area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.
This package provides tools to generate a violin point plot, a combination of a violin/histogram plot and a scatter plot by offsetting points within a category based on their density using quasirandom noise.
This package provides tools to convert the output of utils::getParseData() to an XML tree, that one can search via XPath, and is easier to manipulate in general.
This is a pure R implementation of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) with optional restarts (IPOP-CMA-ES).
This package provides functions for robust principal component analysis (PCA) by projection pursuit.
Testing and documenting code that communicates with remote servers can be painful. This package helps with writing tests for packages that use httr2. It enables testing all of the logic on the R sides of the API without requiring access to the remote service, and it also allows recording real API responses to use as test fixtures. The ability to save responses and load them offline also enables writing vignettes and other dynamic documents that can be distributed without access to a live server.