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r-ggwordcloud
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public |
Provides a word cloud text geom for 'ggplot2'. Texts are placed so that they do not overlap as in 'ggrepel'. The algorithm used is a variation around the one of 'wordcloud2.js'.
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2024-01-16 |
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r-ggraph
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The grammar of graphics as implemented in ggplot2 is a poor fit for graph and network visualizations due to its reliance on tabular data input. ggraph is an extension of the ggplot2 API tailored to graph visualizations and provides the same flexible approach to building up plots layer by layer.
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2024-01-16 |
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r-gldex
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The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution. References include the following: Karvanen and Nuutinen (2008) "Characterizing the generalized lambda distribution by L-moments" <doi:10.1016/j.csda.2007.06.021>, King and MacGillivray (1999) "A starship method for fitting the generalised lambda distributions" <doi:10.1111/1467-842X.00089>, Su (2005) "A Discretized Approach to Flexibly Fit Generalized Lambda Distributions to Data" <doi:10.22237/jmasm/1130803560>, Su (2007) "Nmerical Maximum Log Likelihood Estimation for Generalized Lambda Distributions" <doi:10.1016/j.csda.2006.06.008>, Su (2007) "Fitting Single and Mixture of Generalized Lambda Distributions to Data via Discretized and Maximum Likelihood Methods: GLDEX in R" <doi:10.18637/jss.v021.i09>, Su (2009) "Confidence Intervals for Quantiles Using Generalized Lambda Distributions" <doi:10.1016/j.csda.2009.02.014>, Su (2010) "Chapter 14: Fitting GLDs and Mixture of GLDs to Data using Quantile Matching Method" <doi:10.1201/b10159>, Su (2010) "Chapter 15: Fitting GLD to data using GLDEX 1.0.4 in R" <doi:10.1201/b10159>, Su (2015) "Flexible Parametric Quantile Regression Model" <doi:10.1007/s11222-014-9457-1>, Su (2021) "Flexible parametric accelerated failure time model"<doi:10.1080/10543406.2021.1934854>.
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2024-01-16 |
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r-glcm
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Enables calculation of image textures (Haralick 1973) <doi:10.1109/TSMC.1973.4309314> from grey-level co-occurrence matrices (GLCMs). Supports processing images that cannot fit in memory.
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2024-01-16 |
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r-glassofast
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A fast and improved implementation of the graphical LASSO.
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2024-01-16 |
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r-glasso
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public |
Estimation of a sparse inverse covariance matrix using a lasso (L1) penalty. Facilities are provided for estimates along a path of values for the regularization parameter.
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2024-01-16 |
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r-glamlasso
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Efficient design matrix free lasso penalized estimation in large scale 2 and 3-dimensional generalized linear array model framework. The procedure is based on the gdpg algorithm from Lund et al. (2017) <doi:10.1080/10618600.2017.1279548>. Currently Lasso or Smoothly Clipped Absolute Deviation (SCAD) penalized estimation is possible for the following models: The Gaussian model with identity link, the Binomial model with logit link, the Poisson model with log link and the Gamma model with log link. It is also possible to include a component in the model with non-tensor design e.g an intercept. Also provided are functions, glamlassoRR() and glamlassoS(), fitting special cases of GLAMs.
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2024-01-16 |
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r-ggpointdensity
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A cross between a 2D density plot and a scatter plot, implemented as a 'ggplot2' geom. Points in the scatter plot are colored by the number of neighboring points. This is useful to visualize the 2D-distribution of points in case of overplotting.
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2024-01-16 |
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r-git2r
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None |
Interface to the 'libgit2' library, which is a pure C implementation of the 'Git' core methods. Provides access to 'Git' repositories to extract data and running some basic 'Git' commands.
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2024-01-16 |
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r-giraf
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Allows calculation on, and sampling from Gibbs Random Fields, and more precisely general homogeneous Potts model. The primary tool is the exact computation of the intractable normalising constant for small rectangular lattices. Beside the latter function, it contains method that give exact sample from the likelihood for small enough rectangular lattices or approximate sample from the likelihood using MCMC samplers for large lattices.
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2024-01-16 |
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r-gigrvg
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Generator and density function for the Generalized Inverse Gaussian (GIG) distribution.
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2024-01-16 |
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r-gifi
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Implements categorical principal component analysis ('PRINCALS'), multiple correspondence analysis ('HOMALS'), monotone regression analysis ('MORALS'). It replaces the 'homals' package.
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2024-01-16 |
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r-ghyp
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Detailed functionality for working with the univariate and multivariate Generalized Hyperbolic distribution and its special cases (Hyperbolic (hyp), Normal Inverse Gaussian (NIG), Variance Gamma (VG), skewed Student-t and Gaussian distribution). Especially, it contains fitting procedures, an AIC-based model selection routine, and functions for the computation of density, quantile, probability, random variates, expected shortfall and some portfolio optimization and plotting routines as well as the likelihood ratio test. In addition, it contains the Generalized Inverse Gaussian distribution. See Chapter 3 of A. J. McNeil, R. Frey, and P. Embrechts. Quantitative risk management: Concepts, techniques and tools. Princeton University Press, Princeton (2005).
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2024-01-16 |
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r-ggforce
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The aim of 'ggplot2' is to aid in visual data investigations. This focus has led to a lack of facilities for composing specialised plots. 'ggforce' aims to be a collection of mainly new stats and geoms that fills this gap. All additional functionality is aimed to come through the official extension system so using 'ggforce' should be a stable experience.
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2024-01-16 |
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r-ggrepel
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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.
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2024-01-16 |
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r-ggiraph
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public |
Create interactive 'ggplot2' graphics using 'htmlwidgets'.
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2024-01-16 |
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r-ggmselect
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public |
Graph estimation in Gaussian Graphical Models, following the method developed by C. Giraud, S. Huet and N. Verzelen (2012) <doi:10.1515/1544-6115.1625>. The main functions return the adjacency matrix of an undirected graph estimated from a data matrix.
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2024-01-16 |
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r-ggirread
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Reads data collected from wearable acceleratometers as used in sleep and physical activity research. Currently supports file formats: binary data from 'GENEActiv' <https://activinsights.com/>, binary data from GENEA devices (not for sale), and .cwa-format and .wav-format data from 'Axivity' <https://axivity.com>. Primarily designed to complement R package GGIR <https://CRAN.R-project.org/package=GGIR>.
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2024-01-16 |
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r-gglasso
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A unified algorithm, blockwise-majorization-descent (BMD), for efficiently computing the solution paths of the group-lasso penalized least squares, logistic regression, Huberized SVM and squared SVM. The package is an implementation of Yang, Y. and Zou, H. (2015) DOI: <doi:10.1007/s11222-014-9498-5>.
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2024-01-16 |
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r-getip
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A micro-package for getting your 'IP' address, either the local/internal or the public/external one. Currently only 'IPv4' addresses are supported.
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2024-01-16 |
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r-geos
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public |
Provides an R API to the Open Source Geometry Engine ('GEOS') library (<https://libgeos.org/>) and a vector format with which to efficiently store 'GEOS' geometries. High-performance functions to extract information from, calculate relationships between, and transform geometries are provided. Finally, facilities to import and export geometry vectors to other spatial formats are provided.
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2024-01-16 |
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r-gettz
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A function to retrieve the system timezone on Unix systems which has been found to find an answer when 'Sys.timezone()' has failed. It is based on an answer by Duane McCully posted on 'StackOverflow', and adapted to be callable from R. The package also builds on Windows, but just returns NULL.
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2024-01-16 |
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r-getpass
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A micro-package for reading "passwords", i.e. reading user input with masking, so that the input is not displayed as it is typed. Currently we have support for 'RStudio', the command line (every OS), and any platform where 'tcltk' is present.
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2024-01-16 |
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r-genlasso
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Computes the solution path for generalized lasso problems. Important use cases are the fused lasso over an arbitrary graph, and trend fitting of any given polynomial order. Specialized implementations for the latter two subproblems are given to improve stability and speed. See Taylor Arnold and Ryan Tibshirani (2016) <doi:10.1080/10618600.2015.1008638>.
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2024-01-16 |
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r-geor
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Geostatistical analysis including variogram-based, likelihood-based and Bayesian methods. Software companion for Diggle and Ribeiro (2007) <doi:10.1007/978-0-387-48536-2>.
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2024-01-16 |
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r-gert
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Simple git client for R based on 'libgit2' <https://libgit2.org> with support for SSH and HTTPS remotes. All functions in 'gert' use basic R data types (such as vectors and data-frames) for their arguments and return values. User credentials are shared with command line 'git' through the git-credential store and ssh keys stored on disk or ssh-agent.
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2024-01-16 |
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r-geostatsp
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Geostatistical modelling facilities using 'SpatRaster' and 'SpatVector' objects are provided. Non-Gaussian models are fit using 'INLA', and Gaussian geostatistical models use Maximum Likelihood Estimation. For details see Brown (2015) <doi:10.18637/jss.v063.i12>. The 'RandomFields' package is available at <https://www.wim.uni-mannheim.de/schlather/publications/software>.
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2024-01-16 |
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r-geomap
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public |
Set of routines for making map projections (forward and inverse), topographic maps, perspective plots, geological maps, geological map symbols, geological databases, interactive plotting and selection of focus regions.
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2024-01-16 |
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r-geosphere
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public |
Spherical trigonometry for geographic applications. That is, compute distances and related measures for angular (longitude/latitude) locations.
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2024-01-16 |
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r-geogrid
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public |
Turn irregular polygons (such as geographical regions) into regular or hexagonal grids. This package enables the generation of regular (square) and hexagonal grids through the package 'sp' and then assigns the content of the existing polygons to the new grid using the Hungarian algorithm, Kuhn (1955) (<doi:10.1007/978-3-540-68279-0_2>). This prevents the need for manual generation of hexagonal grids or regular grids that are supposed to reflect existing geography.
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2024-01-16 |
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r-geometry
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Makes the 'Qhull' library <http://www.qhull.org> available in R, in a similar manner as in Octave and MATLAB. Qhull computes convex hulls, Delaunay triangulations, halfspace intersections about a point, Voronoi diagrams, furthest-site Delaunay triangulations, and furthest-site Voronoi diagrams. It runs in 2D, 3D, 4D, and higher dimensions. It implements the Quickhull algorithm for computing the convex hull. Qhull does not support constrained Delaunay triangulations, or mesh generation of non-convex objects, but the package does include some R functions that allow for this.
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2024-01-16 |
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r-geometries
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public |
Geometry shapes in 'R' are typically represented by matrices (points, lines), with more complex shapes being lists of matrices (polygons). 'Geometries' will convert various 'R' objects into these shapes. Conversion functions are available at both the 'R' level, and through 'Rcpp'.
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2024-01-16 |
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r-geojsonsf
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public |
Converts Between GeoJSON and simple feature objects.
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2024-01-16 |
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r-geojsonr
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public |
Includes functions for processing GeoJson objects <https://en.wikipedia.org/wiki/GeoJSON> relying on 'RFC 7946' <https://datatracker.ietf.org/doc/pdf/rfc7946.pdf>. The geojson encoding is based on 'json11', a tiny JSON library for 'C++11' <https://github.com/dropbox/json11>. Furthermore, the source code is exported in R through the 'Rcpp' and 'RcppArmadillo' packages.
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2024-01-16 |
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r-geohashtools
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public |
Tools for working with Gustavo Niemeyer's geohash coordinate system, including API for interacting with other common R GIS libraries.
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2024-01-16 |
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r-geiger
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public |
Methods for fitting macroevolutionary models to phylogenetic trees Pennell (2014) <doi:10.1093/bioinformatics/btu181>.
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2024-01-16 |
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r-geodist
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public |
Dependency-free, ultra fast calculation of geodesic distances. Includes the reference nanometre-accuracy geodesic distances of Karney (2013) <doi:10.1007/s00190-012-0578-z>, as used by the 'sf' package, as well as Haversine and Vincenty distances. Default distance measure is the "Mapbox cheap ruler" which is generally more accurate than Haversine or Vincenty for distances out to a few hundred kilometres, and is considerably faster. The main function accepts one or two inputs in almost any generic rectangular form, and returns either matrices of pairwise distances, or vectors of sequential distances.
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2024-01-16 |
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r-gdina
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A set of psychometric tools for cognitive diagnosis modeling based on the generalized deterministic inputs, noisy and gate (G-DINA) model by de la Torre (2011) <DOI:10.1007/s11336-011-9207-7> and its extensions, including the sequential G-DINA model by Ma and de la Torre (2016) <DOI:10.1111/bmsp.12070> for polytomous responses, and the polytomous G-DINA model by Chen and de la Torre <DOI:10.1177/0146621613479818> for polytomous attributes. Joint attribute distribution can be independent, saturated, higher-order, loglinear smoothed or structured. Q-matrix validation, item and model fit statistics, model comparison at test and item level and differential item functioning can also be conducted. A graphical user interface is also provided. For tutorials, please check Ma and de la Torre (2020) <DOI:10.18637/jss.v093.i14>, Ma and de la Torre (2019) <DOI:10.1111/emip.12262>, Ma (2019) <DOI:10.1007/978-3-030-05584-4_29> and de la Torre and Akbay (2019).
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2024-01-16 |
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r-gensvm
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The GenSVM classifier is a generalized multiclass support vector machine (SVM). This classifier aims to find decision boundaries that separate the classes with as wide a margin as possible. In GenSVM, the loss function is very flexible in the way that misclassifications are penalized. This allows the user to tune the classifier to the dataset at hand and potentially obtain higher classification accuracy than alternative multiclass SVMs. Moreover, this flexibility means that GenSVM has a number of other multiclass SVMs as special cases. One of the other advantages of GenSVM is that it is trained in the primal space, allowing the use of warm starts during optimization. This means that for common tasks such as cross validation or repeated model fitting, GenSVM can be trained very quickly. Based on: G.J.J. van den Burg and P.J.F. Groenen (2018) <https://www.jmlr.org/papers/v17/14-526.html>.
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2024-01-16 |
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r-gensurv
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Generation of survival data with one (binary) time-dependent covariate. Generation of survival data arising from a progressive illness-death model.
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2024-01-16 |
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r-gensa
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public |
Performs search for global minimum of a very complex non-linear objective function with a very large number of optima.
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2024-01-16 |
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r-genodds
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public |
Calculates Agresti's generalized odds ratios. For a randomly selected pair of observations from two groups, calculates the odds that the second group will have a higher scoring outcome than that of the first group. Package provides hypothesis testing for if this odds ratio is significantly different to 1 (equal chance).
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2024-01-16 |
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r-genieclust
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A retake on the Genie algorithm (Gagolewski, 2021 <DOI:10.1016/j.softx.2021.100722>) - a robust hierarchical clustering method (Gagolewski, Bartoszuk, Cena, 2016 <DOI:10.1016/j.ins.2016.05.003>). Now faster and more memory efficient; determining the whole hierarchy for datasets of 10M points in low dimensional Euclidean spaces or 100K points in high-dimensional ones takes only 1-2 minutes. Allows clustering with respect to mutual reachability distances so that it can act as a noise point detector or a robustified version of 'HDBSCAN*' (that is able to detect a predefined number of clusters and hence it does not dependent on the somewhat fragile 'eps' parameter). The package also features an implementation of inequality indices (the Gini, Bonferroni index), external cluster validity measures (e.g., the normalised clustering accuracy and partition similarity scores such as the adjusted Rand, Fowlkes-Mallows, adjusted mutual information, and the pair sets index), and internal cluster validity indices (e.g., the Calinski-Harabasz, Davies-Bouldin, Ball-Hall, Silhouette, and generalised Dunn indices). See also the 'Python' version of 'genieclust' available on 'PyPI', which supports sparse data, more metrics, and even larger datasets.
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2024-01-16 |
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r-genepop
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public |
Makes the Genepop software available in R. This software implements a mixture of traditional population genetic methods and some more focused developments: it computes exact tests for Hardy-Weinberg equilibrium, for population differentiation and for genotypic disequilibrium among pairs of loci; it computes estimates of F-statistics, null allele frequencies, allele size-based statistics for microsatellites, etc.; and it performs analyses of isolation by distance from pairwise comparisons of individuals or population samples.
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2024-01-16 |
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r-genie
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Includes the reference implementation of Genie - a hierarchical clustering algorithm that links two point groups in such a way that an inequity measure (namely, the Gini index) of the cluster sizes does not significantly increase above a given threshold. This method most often outperforms many other data segmentation approaches in terms of clustering quality as tested on a wide range of benchmark datasets. At the same time, Genie retains the high speed of the single linkage approach, therefore it is also suitable for analysing larger data sets. For more details see (Gagolewski et al. 2016 <DOI:10.1016/j.ins.2016.05.003>). For an even faster and more feature-rich implementation, including, amongst others, noise point detection, see the 'genieclust' package.
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2024-01-16 |
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r-genepi
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public |
Package for Genetic Epidemiologic Methods Developed at MSKCC. It contains functions to calculate haplotype specific odds ratio and the power of two stage design for GWAS studies.
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2024-01-16 |
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r-gelnet
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public |
Implements several extensions of the elastic net regularization scheme. These extensions include individual feature penalties for the L1 term, feature-feature penalties for the L2 term, as well as translation coefficients for the latter.
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2024-01-16 |
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r-geigen
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public |
Functions to compute generalized eigenvalues and eigenvectors, the generalized Schur decomposition and the generalized Singular Value Decomposition of a matrix pair, using Lapack routines.
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2024-01-16 |
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r-geepack
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public |
Generalized estimating equations solver for parameters in mean, scale, and correlation structures, through mean link, scale link, and correlation link. Can also handle clustered categorical responses. See e.g. Halekoh and Højsgaard, (2005, <doi:10.18637/jss.v015.i02>), for details.
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2024-01-16 |
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r-gee
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Generalized Estimation Equation solver.
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2024-01-16 |
