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r-combinat
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public |
routines for combinatorics
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2025-04-22 |
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r-colt
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public |
A collection of command-line color styles based on the 'crayon' package. 'Colt' styles are defined in themes that can easily be switched, to ensure command line output looks nice on dark as well as light consoles.
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2025-04-22 |
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r-colr
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Powerful functions to select and rename columns in dataframes, lists and numeric types by 'Perl' regular expression. Regular expression ('regex') are a very powerful grammar to match strings, such as column names.
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2025-04-22 |
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r-colourlovers
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Provides access to the COLOURlovers <http://www.colourlovers.com/> API, which offers color inspiration and color palettes.
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2025-04-22 |
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r-colortools
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R package with handy functions to help users select and play with color schemes in an HSV color model
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2025-04-22 |
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r-colorramps
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Builds gradient color maps
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2025-04-22 |
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r-colorr
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public |
Color palettes for EPL, MLB, NBA, NHL, and NFL teams.
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2025-04-22 |
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r-colorpalette
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Different methods to generate a color palette based on a specified base color and a number of colors that should be created.
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2025-04-22 |
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r-colorhcplot
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public |
Build dendrograms with sample groups highlighted by different colors. Visualize results of hierarchical clustering analyses as dendrograms whose leaves and labels are colored according to sample grouping. Assess whether data point grouping aligns to naturally occurring clusters.
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2025-04-22 |
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r-colorfulvennplot
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Given 2-,3- or 4-dimensional data, plots a Venn diagram, i.e. 'crossing circles'. The user can specify values, labels for each circle-group and unique colors for each plotted part. Here is what it would look like for a 3-dimensional plot: http://elliotnoma.files.wordpress.com/2011/02/venndiagram.png. To see what the 4-dimensional plot looks like, go to http://elliotnoma.files.wordpress.com/2013/03/4dplot.png.
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2025-04-22 |
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r-coloredica
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It implements colored Independent Component Analysis (Lee et al., 2011) and spatial colored Independent Component Analysis (Shen et al., 2014). They are two algorithms to perform ICA when sources are assumed to be temporal or spatial stochastic processes, respectively.
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2025-04-22 |
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r-colmozzie
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Weekly notified dengue cases and climate variables in Colombo district Sri Lanka from 2008/ week-52 to 2014/ week-21.
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2025-04-22 |
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r-collesslike
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Computation of Colless-Like, Sackin and cophenetic balance indices of a phylogenetic tree and study of the distribution of these balance indices under the alpha-gamma model. For more details see A. Mir, F. Rossello, L. Rotger (2013) <doi:10.1016/j.mbs.2012.10.005>, M. J. Sackin (1972) <doi:10.1093/sysbio/21.2.225>, D. H. Colless (1982) <doi:10.2307/2413420>.
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2025-04-22 |
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r-collectargs
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We often want to take all (or most) of the objects in one environment (such as the parameter values of a function) and pass them to another. This might be calling a second function, or iterating over a list, calling the same function. These functions wrap often repeated code. Current stable version (committed on October 14, 2017).
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2025-04-22 |
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r-cointreg
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Cointegration methods are widely used in empirical macroeconomics and empirical finance. It is well known that in a cointegrating regression the ordinary least squares (OLS) estimator of the parameters is super-consistent, i.e. converges at rate equal to the sample size T. When the regressors are endogenous, the limiting distribution of the OLS estimator is contaminated by so-called second order bias terms, see e.g. Phillips and Hansen (1990) <DOI:10.2307/2297545>. The presence of these bias terms renders inference difficult. Consequently, several modifications to OLS that lead to zero mean Gaussian mixture limiting distributions have been proposed, which in turn make standard asymptotic inference feasible. These methods include the fully modified OLS (FM-OLS) approach of Phillips and Hansen (1990) <DOI:10.2307/2297545>, the dynamic OLS (D-OLS) approach of Phillips and Loretan (1991) <DOI:10.2307/2298004>, Saikkonen (1991) <DOI:10.1017/S0266466600004217> and Stock and Watson (1993) <DOI:10.2307/2951763> and the new estimation approach called integrated modified OLS (IM-OLS) of Vogelsang and Wagner (2014) <DOI:10.1016/j.jeconom.2013.10.015>. The latter is based on an augmented partial sum (integration) transformation of the regression model. IM-OLS is similar in spirit to the FM- and D-OLS approaches, with the key difference that it does not require estimation of long run variance matrices and avoids the need to choose tuning parameters (kernels, bandwidths, lags). However, inference does require that a long run variance be scaled out. This package provides functions for the parameter estimation and inference with all three modified OLS approaches. That includes the automatic bandwidth selection approaches of Andrews (1991) <DOI:10.2307/2938229> and of Newey and West (1994) <DOI:10.2307/2297912> as well as the calculation of the long run variance.
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2025-04-22 |
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r-coindeskr
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Extract real-time Bitcoin price details by accessing 'CoinDesk' Bitcoin price Index API <https://www.coindesk.com/api/>.
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2025-04-22 |
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r-cofra
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Calculates complete functional regulation analysis and visualize the results in a single heatmap. The provided example data is for biological data but the methodology can be used for large data sets to compare quantitative entities that can be grouped. For example, a store might divide entities into cloth, food, car products etc and want to see how sales changes in the groups after some event. The theoretical background for the calculations are provided in New insights into functional regulation in MS-based drug profiling, Ana Sofia Carvalho, Henrik Molina & Rune Matthiesen, Scientific Reports <doi:10.1038/srep18826>.
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2025-04-22 |
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r-cofad
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Contrast analysis for factorial designs is an alternative to the classical ANOVA approach with the advantage of testing focused hypothesis. The method is mainly based on Rosenthal, Rosnow and Rubin (2000, ISBN:978-0521659802) and Sedlmeier and Renkewitz (2018, ISBN:978-3868943214).
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2025-04-22 |
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r-coexist
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species coexistence modeling under asymmetric dispersal and fluctuating source-sink dynamics;testing the proportion of coexistence scenarios driven by neutral and niche processes
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2025-04-22 |
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r-coenocliner
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Simulate species occurrence and abundances (counts) along gradients.
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2025-04-22 |
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r-codina
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Categorize links and nodes from multiple networks in 3 categories: Common links (alpha) specific links (gamma), and different links (beta). Also categorizes the links into sub-categories and groups. The package includes a visualization tool for the networks. More information about the methodology can be found at: Gysi et. al., 2018 <arXiv:1802.00828>.
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2025-04-22 |
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r-code
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Generates all necessary C functions allowing the user to work with the compiled-code interface of ode() and bvptwp(). The implementation supports "forcings" and "events". Also provides functions to symbolically compute Jacobians, sensitivity equations and adjoint sensitivities being the basis for sensitivity analysis.
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2025-04-22 |
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r-codatags
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Computes genomic breeding values using external information on the markers. The package fits a linear mixed model with heteroscedastic random effects, where the random effect variance is fitted using a linear predictor and a log link. The method is described in Mouresan, Selle and Ronnegard (2019) <doi:10.1101/636746>.
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2025-04-22 |
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r-cocron
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Statistical tests for the comparison between two or more alpha coefficients based on either dependent or independent groups of individuals. A web interface is available at http://comparingcronbachalphas.org. A plugin for the R GUI and IDE RKWard is included. Please install RKWard from https:// rkward.kde.org to use this feature. The respective R package 'rkward' cannot be installed directly from a repository, as it is a part of RKWard.
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2025-04-22 |
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r-cocor
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Statistical tests for the comparison between two correlations based on either independent or dependent groups. Dependent correlations can either be overlapping or nonoverlapping. A web interface is available on the website http://comparingcorrelations.org. A plugin for the R GUI and IDE RKWard is included. Please install RKWard from https://rkward.kde.org to use this feature. The respective R package 'rkward' cannot be installed directly from a repository, as it is a part of RKWard.
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2025-04-22 |
