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/_/ /      / / /____\/ /       \ \_\\ \/___/ /
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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.


r-krls 1.0-0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://www.r-project.org
Licenses: GPL 2+
Synopsis: Kernel-Based Regularized Least Squares
Description:

Package implements Kernel-based Regularized Least Squares (KRLS), a machine learning method to fit multidimensional functions y=f(x) for regression and classification problems without relying on linearity or additivity assumptions. KRLS finds the best fitting function by minimizing the squared loss of a Tikhonov regularization problem, using Gaussian kernels as radial basis functions. For further details see Hainmueller and Hazlett (2014).

r-kdemcmc 0.0.2
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KDEmcmc
Licenses: GPL 3+
Synopsis: Kernel Density Estimation with a Markov Chain Monte Carlo Sample
Description:

This package provides methods for selecting the optimal bandwidth in kernel density estimation for dependent samples, such as those generated by Markov chain Monte Carlo (MCMC). Implements a modified biased cross-validation (mBCV) approach that accounts for sample dependence, improving the accuracy of estimated density functions.

r-knotr 1.0-4
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=knotR
Licenses: GPL 2
Synopsis: Knot Diagrams using Bezier Curves
Description:

Makes visually pleasing diagrams of knot projections using optimized Bezier curves.

r-kappasize 1.2
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kappaSize
Licenses: GPL 2+
Synopsis: Sample Size Estimation Functions for Studies of Interobserver Agreement
Description:

This package contains basic tools for sample size estimation in studies of interobserver/interrater agreement (reliability). Includes functions for both the power-based and confidence interval-based methods, with binary or multinomial outcomes and two through six raters.

r-klsh 0.1.0
Propagated dependencies: r-stringi@1.8.7 r-snowballc@0.7.1 r-rcpp@1.1.0 r-plyr@1.8.9 r-blink@1.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=klsh
Licenses: GPL 3
Synopsis: Blocking for Record Linkage
Description:

An implementation of the blocking algorithm KLSH in Steorts, Ventura, Sadinle, Fienberg (2014) <DOI:10.1007/978-3-319-11257-2_20>, which is a k-means variant of locality sensitive hashing. The method is illustrated with examples and a vignette.

r-kirby21-base 1.7.3
Propagated dependencies: r-git2r@0.36.2
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://www.nitrc.org/projects/multimodal/
Licenses: GPL 2
Synopsis: Example Data from the Multi-Modal MRI 'Reproducibility' Resource
Description:

Multi-modal magnetic resonance imaging ('MRI') data from the Kirby21 reproducibility study <https://www.nitrc.org/projects/multimodal/>, including functional and structural imaging.

r-keyboardsimulator 2.6.2
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/ChiHangChen/KeyboardSimulator
Licenses: GPL 2+ FSDG-compatible
Synopsis: Keyboard and Mouse Input Simulation for Windows OS
Description:

Control your keyboard and mouse with R code by simulating key presses and mouse clicks. The input simulation is implemented with the Windows API.

r-kor-addrlink 1.0.1
Propagated dependencies: r-stringi@1.8.7 r-stringdist@0.9.15
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://git-kor.stadtdo.de
Licenses: GPL 3
Synopsis: Matching Address Data to Reference Index
Description:

Matches a data set with semi-structured address data, e.g., street and house number as a concatenated string, wrongly spelled street names or non-existing house numbers to a reference index. The methods are specifically designed for German municipalities ('KOR'-community) and German address schemes.

r-kssa 0.0.5
Propagated dependencies: r-zoo@1.8-14 r-rlang@1.1.6 r-missmethods@0.4.0 r-metrics@0.1.4 r-magrittr@2.0.4 r-imputets@3.4 r-ggplot2@4.0.1 r-forecast@8.24.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/steffenmoritz/kssa
Licenses: AGPL 3+
Synopsis: Known Sub-Sequence Algorithm
Description:

This package implements the Known Sub-Sequence Algorithm <doi:10.1016/j.aaf.2021.12.013>, which helps to automatically identify and validate the best method for missing data imputation in a time series. Supports the comparison of multiple state-of-the-art algorithms.

r-kere 1.0.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KERE
Licenses: GPL 2
Synopsis: Expectile Regression in Reproducing Kernel Hilbert Space
Description:

An efficient algorithm inspired by majorization-minimization principle for solving the entire solution path of a flexible nonparametric expectile regression estimator constructed in a reproducing kernel Hilbert space.

r-kendallrandomwalks 0.9.4
Propagated dependencies: r-tibble@3.3.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-actuar@3.3-6
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kendallRandomWalks
Licenses: Expat
Synopsis: Simulate and Visualize Kendall Random Walks and Related Distributions
Description:

Kendall random walks are a continuous-space Markov chains generated by the Kendall generalized convolution. This package provides tools for simulating these random walks and studying distributions related to them. For more information about Kendall random walks see Jasiulis-GoÅ dyn (2014) <arXiv:1412.0220>.

r-kris 1.1.6
Propagated dependencies: r-rarpack@0.11-0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://gitlab.com/kris.ccp/kris
Licenses: Expat
Synopsis: Keen and Reliable Interface Subroutines for Bioinformatic Analysis
Description:

This package provides useful functions which are needed for bioinformatic analysis such as calculating linear principal components from numeric data and Single-nucleotide polymorphism (SNP) dataset, calculating fixation index (Fst) using Hudson method, creating scatter plots in 3 views, handling with PLINK binary file format, detecting rough structures and outliers using unsupervised clustering, and calculating matrix multiplication in the faster way for big data.

r-kim 0.6.1
Propagated dependencies: r-remotes@2.5.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/jinkim3/kim
Licenses: GPL 3
Synopsis: Toolkit for Behavioral Scientists
Description:

This package provides a collection of functions for analyzing data typically collected or used by behavioral scientists. Examples of the functions include a function that compares groups in a factorial experimental design, a function that conducts two-way analysis of variance (ANOVA), and a function that cleans a data set generated by Qualtrics surveys. Some of the functions will require installing additional package(s). Such packages and other references are cited within the section describing the relevant functions. Many functions in this package rely heavily on these two popular R packages: Dowle et al. (2021) <https://CRAN.R-project.org/package=data.table>. Wickham et al. (2021) <https://CRAN.R-project.org/package=ggplot2>.

r-khroma 1.17.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://codeberg.org/tesselle/khroma
Licenses: GPL 3+
Synopsis: Colour Schemes for Scientific Data Visualization
Description:

Color schemes ready for each type of data (qualitative, diverging or sequential), with colors that are distinct for all people, including color-blind readers. This package provides an implementation of Paul Tol (2018) and Fabio Crameri (2018) <doi:10.5194/gmd-11-2541-2018> color schemes for use with graphics or ggplot2'. It provides tools to simulate color-blindness and to test how well the colors of any palette are identifiable. Several scientific thematic schemes (geologic timescale, land cover, FAO soils, etc.) are also implemented.

r-kpodclustr 1.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: http://jocelynchi.com/kpodclustr
Licenses: Expat
Synopsis: Method for Clustering Partially Observed Data
Description:

Software for k-means clustering of partially observed data from Chi, Chi, and Baraniuk (2016) <doi:10.1080/00031305.2015.1086685>.

r-kriging 1.2
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kriging
Licenses: GPL 2
Synopsis: Ordinary Kriging
Description:

An implementation of a simple and highly optimized ordinary kriging algorithm to plot geographical data.

r-kspm 0.2.1
Propagated dependencies: r-expm@1.0-0 r-deoptim@2.2-8 r-compquadform@1.4.4
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KSPM
Licenses: GPL 3
Synopsis: Kernel Semi-Parametric Models
Description:

To fit the kernel semi-parametric model and its extensions. It allows multiple kernels and unlimited interactions in the same model. Coefficients are estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters are estimated by minimizing leave-one-out error. It includes predictions with confidence/prediction intervals, statistical tests for the significance of each kernel, a procedure for variable selection and graphical tools for diagnostics and interpretation of covariate effects. Currently it is implemented for continuous dependent variables. The package is based on the paper of Liu et al. (2007), <doi:10.1111/j.1541-0420.2007.00799.x>.

r-konfound 1.0.3
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-ppcor@1.1 r-pbkrtest@0.5.5 r-lme4@1.1-37 r-lavaan@0.6-20 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-crayon@1.5.3 r-broom-mixed@0.2.9.6 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/konfound-project/konfound
Licenses: Expat
Synopsis: Quantify the Robustness of Causal Inferences
Description:

Statistical methods that quantify the conditions necessary to alter inferences, also known as sensitivity analysis, are becoming increasingly important to a variety of quantitative sciences. A series of recent works, including Frank (2000) <doi:10.1177/0049124100029002001> and Frank et al. (2013) <doi:10.3102/0162373713493129> extend previous sensitivity analyses by considering the characteristics of omitted variables or unobserved cases that would change an inference if such variables or cases were observed. These analyses generate statements such as "an omitted variable would have to be correlated at xx with the predictor of interest (e.g., the treatment) and outcome to invalidate an inference of a treatment effect". Or "one would have to replace pp percent of the observed data with nor which the treatment had no effect to invalidate the inference". We implement these recent developments of sensitivity analysis and provide modules to calculate these two robustness indices and generate such statements in R. In particular, the functions konfound(), pkonfound() and mkonfound() allow users to calculate the robustness of inferences for a user's own model, a single published study and multiple studies respectively.

r-keras 2.16.0
Propagated dependencies: r-zeallot@0.2.0 r-tfruns@1.5.4 r-tensorflow@2.20.0 r-rlang@1.1.6 r-reticulate@1.44.1 r-r6@2.6.1 r-magrittr@2.0.4 r-glue@1.8.0 r-generics@0.1.4
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://tensorflow.rstudio.com/
Licenses: Expat
Synopsis: R Interface to 'Keras'
Description:

Interface to Keras <https://keras.io>, a high-level neural networks API'. Keras was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both CPU and GPU devices.

r-kvkapir 0.1.2
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-purrr@1.2.0 r-lifecycle@1.0.4 r-httr2@1.2.1 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://coeneisma.github.io/kvkapiR/
Licenses: Expat
Synopsis: Interface to the Dutch Chamber of Commerce (KvK) API
Description:

Access business registration data from the Dutch Chamber of Commerce (Kamer van Koophandel, KvK) through their official API <https://developers.kvk.nl/>. Search for companies by name, location, or registration number. Retrieve detailed business profiles, establishment information, and company name histories. Built on httr2 for robust API interaction with automatic pagination, error handling, and usage tracking.

r-knitrdata 0.6.2
Propagated dependencies: r-xfun@0.54 r-knitr@1.50
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/dmkaplan2000/knitrdata
Licenses: GPL 3
Synopsis: Data Language Engine for 'knitr' / 'rmarkdown'
Description:

This package implements a data language engine for incorporating data directly in rmarkdown documents so that they can be made completely standalone.

r-kimfilter 1.1.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kimfilter
Licenses: GPL 2+
Synopsis: Kim Filter
Description:

Rcpp implementation of the multivariate Kim filter, which combines the Kalman and Hamilton filters for state probability inference. The filter is designed for state space models and can handle missing values and exogenous data in the observation and state equations. Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.

r-kinesis 0.3.1
Propagated dependencies: r-tabula@3.3.2 r-shiny@1.11.1 r-sass@0.4.10 r-nexus@0.6.0 r-mirai@2.5.2 r-khroma@1.17.0 r-kairos@2.3.0 r-isopleuros@1.4.0 r-gt@1.2.0 r-dimensio@0.14.1 r-config@0.3.2 r-bslib@0.9.0 r-arkhe@1.11.0 r-aion@1.6.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://codeberg.org/tesselle/kinesis
Licenses: GPL 3+
Synopsis: 'shiny' Applications for the 'tesselle' Packages
Description:

This package provides a collection of shiny applications for the tesselle packages <https://www.tesselle.org/>. This package provides applications for archaeological data analysis and visualization. These mainly, but not exclusively, include applications for chronological modelling (e.g. matrix seriation, aoristic analysis) and count data analysis (e.g. diversity measures, compositional data analysis).

r-kdps 1.0.0
Propagated dependencies: r-tibble@3.3.0 r-progress@1.2.3 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/UCSD-Salem-Lab/kdps
Licenses: Expat
Synopsis: Kinship Decouple and Phenotype Selection (KDPS)
Description:

This package provides a phenotype-aware algorithm for resolving cryptic relatedness in genetic studies. It removes related individuals based on kinship or identity-by-descent (IBD) scores while prioritizing subjects with phenotypes of interest. This approach helps maximize the retention of informative subjects, particularly for rare or valuable traits, and improves statistical power in genetic and epidemiological studies. KDPS supports both categorical and quantitative phenotypes, composite scoring, and customizable pruning strategies using a fuzziness parameter. Benchmark results show improved phenotype retention and high computational efficiency on large-scale datasets like the UK Biobank. Methods used include Manichaikul et al. (2010) <doi:10.1093/bioinformatics/btq559> for kinship estimation, Purcell et al. (2007) <doi:10.1086/519795> for IBD estimation, and Bycroft et al. (2018) <doi:10.1038/s41586-018-0579-z> for UK Biobank data reference.

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Total results: 68249