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Rapidly create a GUI for a function you created by automatically creating widgets for arguments of the function. This package automatically parses help routines for context-sensitive help to these arguments. The interface is essentially a wrapper to some Tcl/Tk routines to both simplify and facilitate GUI creation. More advanced Tcl/Tk routines/GUI objects can be incorporated into the interface for greater customization for the more experienced.
This package provides drop-in replacements for the base system2() function with fine control and consistent behavior across platforms. It supports clean interruption, timeout, background tasks, and streaming STDIN / STDOUT / STDERR over binary or text connections. The package also provides functions for evaluating expressions inside a temporary fork. Such evaluations have no side effects on the main R process, and support reliable interrupts and timeouts. This provides the basis for a sandboxing mechanism.
This package provides an interface to lm.wfit for fitting dynamic linear models and time series regression relationships.
This package processes accelerometer data from uni-axial and tri-axial devices and generates data summaries. Also, includes functions to plot, analyze, and simulate accelerometer data.
This package implements Barzilai-Borwein spectral methods for solving nonlinear system of equations, and for optimizing nonlinear objective functions subject to simple constraints.
This package provides simple functions to compute and plot two types (sample-size- and coverage-based) rarefaction and extrapolation curves for species diversity (Hill numbers) based on individual-based abundance data or sampling-unit- based incidence data; see Chao and others (2014, Ecological Monographs) for pertinent theory and methodologies, and Hsieh, Ma and Chao (2016, Methods in Ecology and Evolution) for an introduction of the R package.
This package provides the datasets to support the Fish Stock Assessment (FSA) package.
This package computes the areas under the precision-recall (PR) and ROC curve for weighted (e.g. soft-labeled) and unweighted data. In contrast to other implementations, the interpolation between points of the PR curve is done by a non-linear piecewise function. In addition to the areas under the curves, the curves themselves can also be computed and plotted by a specific S3-method.
This a package containing diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. It includes R data of class sf, Spatial, and nb. It also contains data stored in a range of file formats including GeoJSON, ESRI Shapefile and GeoPackage. Some of the datasets are designed to illustrate specific analysis techniques. cycle_hire() and cycle_hire_osm(), for example, are designed to illustrate point pattern analysis techniques.
The grammar of graphics as shown in ggplot2 has provided an expressive API for users to build plots. This package ggside extends ggplot2 by allowing users to add graphical information about one of the main panel's axis using a familiar ggplot2 style API with tidy data. This package is particularly useful for visualizing metadata on a discrete axis, or summary graphics on a continuous axis such as a boxplot or a density distribution.
This package contains linear and nonlinear regression methods based on partial least squares and penalization techniques. Model parameters are selected via cross-validation, and confidence intervals ans tests for the regression coefficients can be conducted via jackknifing.
This package provides Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of RcppArmadillo to speed up the computationally intensive parts of the functions. For more information, see
"Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, https://doi.org/10.18637/jss.v001.i04;
"Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, https://doi.org/10.1145/1772690.1772862;
"Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, https://doi.org/10.21105/joss.00026;
"Clustering by Passing Messages Between Data Points" by Brendan J. Frey and Delbert Dueck, Science 16 Feb 2007: Vol. 315, Issue 5814, pp. 972-976, https://doi.org/10.1126/science.1136800.
This package provides MathJax and macros to enable its use within Rd files for rendering equations in the HTML help files.
This package provides miscellaneous functions to help customize ggplot2 objects. High-level functions are provided to post-process ggplot2 layouts and allow alignment between plot panels, as well as setting panel sizes to fixed values. Other functions include a custom geom, and helper functions to enforce symmetric scales or add tags to facetted plots.
Low-rank matrix decompositions are fundamental tools and widely used for data analysis, dimension reduction, and data compression. Classically, highly accurate deterministic matrix algorithms are used for this task. However, the emergence of large-scale data has severely challenged our computational ability to analyze big data. The concept of randomness has been demonstrated as an effective strategy to quickly produce approximate answers to familiar problems such as the singular value decomposition (SVD). This package provides several randomized matrix algorithms such as the randomized singular value decomposition (rsvd), randomized principal component analysis (rpca), randomized robust principal component analysis (rrpca), randomized interpolative decomposition (rid), and the randomized CUR decomposition (rcur). In addition several plot functions are provided.
colorout is an R package that colorizes R output when running in terminal emulator.
R STDOUT is parsed and numbers, negative numbers, dates in the standard format, strings, and R constants are identified and wrapped by special ANSI scape codes that are interpreted by terminal emulators as commands to colorize the output. R STDERR is also parsed to identify the expressions warning and error and their translations to many languages. If these expressions are found, the output is colorized accordingly; otherwise, it is colorized as STDERROR (blue, by default).
You can customize the colors according to your taste, guided by the color table made by the command show256Colors(). You can also set the colors to any arbitrary string. In this case, it is up to you to set valid values.
This package provides tools to create themes and color palettes for the package ggplot2.
Models can be improved by post-processing class probabilities, by: recalibration, conversion to hard probabilities, assessment of equivocal zones, and other activities. The probably package contains tools for conducting these operations as well as calibration tools and conformal inference techniques for regression models.
This package provides a collection of miscellaneous 3d plots, including isosurfaces.
This package provides cover-tree and kd-tree fast k-nearest neighbor search algorithms. Related applications including KNN classification, regression and information measures are implemented.
Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press).
Similarly to the FNN package, this package allows calculation of the k nearest neighbors (kNN) of a data matrix. The implementation is based on cover trees introduced by Alina Beygelzimer, Sham Kakade, and John Langford (2006) doi:10.1145/1143844.1143857.
This package provides a set of utilities for client/server computing with R, controlling a remote R session (the server) from a local one (the client).
This package provides a ggplot2 extension for implementing parliament charts and several other useful visualizations.