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r-rferns
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public |
Provides the random ferns classifier by Ozuysal, Calonder, Lepetit and Fua (2009) <doi:10.1109/TPAMI.2009.23>, modified for generic and multi-label classification and featuring OOB error approximation and importance measure as introduced in Kursa (2014) <doi:10.18637/jss.v061.i10>.
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2025-09-24 |
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r-qdap
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public |
Automates many of the tasks associated with quantitative discourse analysis of transcripts containing discourse including frequency counts of sentence types, words, sentences, turns of talk, syllables and other assorted analysis tasks. The package provides parsing tools for preparing transcript data. Many functions enable the user to aggregate data by any number of grouping variables, providing analysis and seamless integration with other R packages that undertake higher level analysis and visualization of text. This affords the user a more efficient and targeted analysis. 'qdap' is designed for transcript analysis, however, many functions are applicable to other areas of Text Mining/ Natural Language Processing.
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2025-09-24 |
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r-shinymatrix
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public |
Implements a custom matrix input field.
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2025-09-24 |
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r-glpkapi
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public |
R Interface to C API of GLPK, depends on GLPK Version >= 4.42.
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2025-09-24 |
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r-genlasso
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public |
Provides fast algorithms for computing 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 problems are given to improve stability and speed.
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2025-09-24 |
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r-ggconf
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public |
A flexible interface for ggplot2::theme(), potentially saving 50% of your typing.
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2025-09-24 |
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r-plackettluce
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public |
Functions to prepare rankings data and fit the Plackett-Luce model jointly attributed to Plackett (1975) <doi:10.2307/2346567> and Luce (1959, ISBN:0486441369). The standard Plackett-Luce model is generalized to accommodate ties of any order in the ranking. Partial rankings, in which only a subset of items are ranked in each ranking, are also accommodated in the implementation. Disconnected/weakly connected networks implied by the rankings may be handled by adding pseudo-rankings with a hypothetical item. Optionally, a multivariate normal prior may be set on the log-worth parameters and ranker reliabilities may be incorporated as proposed by Raman and Joachims (2014) <doi:10.1145/2623330.2623654>. Maximum a posteriori estimation is used when priors are set. Methods are provided to estimate standard errors or quasi-standard errors for inference as well as to fit Plackett-Luce trees. See the package website or vignette for further details.
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2025-09-24 |
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tiledb
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public |
TileDB sparse and dense multi-dimensional array data management
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2025-09-24 |
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mastodon.py
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public |
Python wrapper for the Mastodon API
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2025-09-24 |
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r-hdci
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public |
Fits regression models on high dimensional data to estimate coefficients and use bootstrap method to obtain confidence intervals. Choices for regression models are Lasso, Lasso+OLS, Lasso partial ridge, Lasso+OLS partial ridge.
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2025-09-24 |
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r-utility
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public |
Construct and plot objective hierarchies and associated value and utility functions. Evaluate the values and utilities and visualize the results as colored objective hierarchies or tables. Visualize uncertainty by plotting median and quantile intervals within the nodes of objective hierarchies. Get numerical results of the evaluations in standard R data types for further processing.
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2025-09-24 |
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r-dendroextras
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public |
Provides extra functions to manipulate dendrograms that build on the base functions provided by the 'stats' package. The main functionality it is designed to add is the ability to colour all the edges in an object of class 'dendrogram' according to cluster membership i.e. each subtree is coloured, not just the terminal leaves. In addition it provides some utility functions to cut 'dendrogram' and 'hclust' objects and to set/get labels.
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2025-09-24 |
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r-rmsnumpress
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public |
'Rcpp' bindings to the native C++ implementation of MS Numpress, that provides two compression schemes for numeric data from mass spectrometers. The library provides implementations of 3 different algorithms, 1 designed to compress first order smooth data like retention time or M/Z arrays, and 2 for compressing non smooth data with lower requirements on precision like ion count arrays. Refer to the publication (Teleman et al., (2014) <doi:10.1074/mcp.O114.037879>) for more details.
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2025-09-24 |
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r-repo
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public |
A data manager meant to avoid manual storage/retrieval of data to/from the file system. It builds one (or more) centralized repository where R objects are stored with rich annotations, including corresponding code chunks, and easily searched and retrieved.
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2025-09-24 |
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r-diagrammer
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public |
Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges.
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2025-09-24 |
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r-bio3d
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public |
Utilities to process, organize and explore protein structure, sequence and dynamics data. Features include the ability to read and write structure, sequence and dynamic trajectory data, perform sequence and structure database searches, data summaries, atom selection, alignment, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, normal mode analysis, principal component analysis of heterogeneous structure data, and correlation network analysis from normal mode and molecular dynamics data. In addition, various utility functions are provided to enable the statistical and graphical power of the R environment to work with biological sequence and structural data. Please refer to the URLs below for more information.
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2025-09-24 |
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r-extrafont
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public |
Tools to using fonts other than the standard PostScript fonts. This package makes it easy to use system TrueType fonts and with PDF or PostScript output files, and with bitmap output files in Windows. extrafont can also be used with fonts packaged specifically to be used with, such as the fontcm package, which has Computer Modern PostScript fonts with math symbols. See https://github.com/wch/extrafont for instructions and examples.
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2025-09-24 |
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hdlib
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public |
hdlib
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2025-09-24 |
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r-robust
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public |
Methods for robust statistics, a state of the art in the early 2000s, notably for robust regression and robust multivariate analysis.
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2025-09-24 |
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fractal-task-tools
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public |
Shared tools for Fractal tasks
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2025-09-24 |
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epics-base-static-libs
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public |
EPICS Base Library
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2025-09-24 |
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epics-base
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public |
EPICS Base Library
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2025-09-24 |
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libtirpc
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public |
Libtirpc is a Transport-Independent RPC library for Linux
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2025-09-24 |
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r-fedmatch
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public |
Provides a flexible set of tools for matching two un-linked data sets. 'fedmatch' allows for three ways to match data: exact matches, fuzzy matches, and multi-variable matches. It also allows an easy combination of these three matches via the tier matching function.
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2025-09-24 |
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r-puniform
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public |
Provides meta-analysis methods that correct for publication bias and outcome reporting bias. Four methods and a visual tool are currently included in the package. The p-uniform method as described in van Assen, van Aert, and Wicherts (2015) <https:psycnet.apa.org/record/2014-48759-001> can be used for estimating the average effect size, testing the null hypothesis of no effect, and testing for publication bias using only the statistically significant effect sizes of primary studies. The second method in the package is the p-uniform* method as described in van Aert and van Assen (2019) <doi:10.31222/osf.io/zqjr9>. This method is an extension of the p-uniform method that allows for estimation of the average effect size and the between-study variance in a meta-analysis, and uses both the statistically significant and nonsignificant effect sizes. The third method in the package is the hybrid method as described in van Aert and van Assen (2017) <doi:10.3758/s13428-017-0967-6>. The hybrid method is a meta-analysis method for combining an original study and replication and while taking into account statistical significance of the original study. The p-uniform and hybrid method are based on the statistical theory that the distribution of p-values is uniform conditional on the population effect size. The fourth method in the package is the Snapshot Bayesian Hybrid Meta-Analysis Method as described in van Aert and van Assen (2018) <doi:10.1371/journal.pone.0175302>. This method computes posterior probabilities for four true effect sizes (no, small, medium, and large) based on an original study and replication while taking into account publication bias in the original study. The method can also be used for computing the required sample size of the replication akin to power analysis in null hypothesis significance testing. The meta-plot is a visual tool for meta-analysis that provides information on the primary studies in the meta-analysis, the results of the meta-analysis, and characteristics of the research on the effect under study (van Assen et al., 2021). Helper functions to apply the Correcting for Outcome Reporting Bias (CORB) method to correct for outcome reporting bias in a meta-analysis (van Aert & Wicherts, 2021).
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2025-09-24 |
