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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-klexp 1.0.0
Propagated dependencies: r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/Zongrui-Dai/Kernel-lasso-feature-expansion
Licenses: GPL 2
Synopsis: Kernel_lasso Expansion
Description:

This package provides the function to calculate the kernel-lasso expansion, Z-score, and max-min-scale standardization.It can increase the dimension of existed dataset and remove abundant features by lasso. Z Dai, L Jiayi, T Gong, C Wang (2021) <doi:10.1088/1742-6596/1955/1/012047>.

r-kbmvtskew 1.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KbMvtSkew
Licenses: GPL 3+
Synopsis: Khattree-Bahuguna's Univariate and Multivariate Skewness
Description:

Computes Khattree-Bahuguna's univariate and multivariate skewness, principal-component-based Khattree-Bahuguna's multivariate skewness. It also provides several measures of univariate or multivariate skewnesses including, Pearsonâ s coefficient of skewness, Bowleyâ s univariate skewness and Mardia's multivariate skewness. See Khattree, R. and Bahuguna, M. (2019) <doi: 10.1007/s41060-018-0106-1>.

r-knockoffhybrid 1.0.1
Propagated dependencies: r-spatest@3.1.2 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KnockoffHybrid
Licenses: GPL 3
Synopsis: Hybrid Analysis of Population and Trio Data with Knockoff Statistics for FDR Control
Description:

Identification of putative causal variants in genome-wide association studies using hybrid analysis of both the trio and population designs. The package implements the method in the paper: Yang, Y., Wang, Q., Wang, C., Buxbaum, J., & Ionita-Laza, I. (2024). KnockoffHybrid: A knockoff framework for hybrid analysis of trio and population designs in genome-wide association studies. The American Journal of Human Genetics, in press.

r-kerdiest 1.3-1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kerdiest
Licenses: GPL 2+
Synopsis: Nonparametric Kernel Estimation of Distribution Function
Description:

Nonparametric kernel distribution function estimation is performed. Three bandwidth selectors are implemented: the plug-in selectors of Altman and Leger and of Polansky and Baker, and the cross-validation selector of Bowman, Hall and Prvan. The exceedance function, the mean return period and the return level are also computed. For details, see Quintela-del-Rà o and Estévez-Pérez (2012) <doi:10.18637/jss.v050.i08>.

r-kairos 2.3.0
Propagated dependencies: r-extradistr@1.10.0 r-dimensio@0.14.1 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/kairos
Licenses: GPL 3+
Synopsis: Analysis of Chronological Patterns from Archaeological Count Data
Description:

This package provides a toolkit for absolute and relative dating and analysis of chronological patterns. This package includes functions for chronological modeling and dating of archaeological assemblages from count data. It provides methods for matrix seriation. It also allows to compute time point estimates and density estimates of the occupation and duration of an archaeological site.

r-knnvs 0.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kNNvs
Licenses: GPL 3
Synopsis: k Nearest Neighbors with Grid Search Variable Selection
Description:

k Nearest Neighbors with variable selection, combine grid search and forward selection to achieve variable selection in order to improve k Nearest Neighbors predictive performance.

r-keng 2025.10.8
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/qyaozh/Keng
Licenses: FSDG-compatible
Synopsis: Knock Errors Off Nice Guesses
Description:

Miscellaneous functions and data used in psychological research and teaching. Keng currently has a built-in dataset depress, and could (1) scale a vector; (2) compute the cut-off values of Pearson's r with known sample size; (3) test the significance and compute the post-hoc power for Pearson's r with known sample size; (4) conduct a priori power analysis and plan the sample size for Pearson's r; (5) compare lm()'s fitted outputs using R-squared, f_squared, post-hoc power, and PRE (Proportional Reduction in Error, also called partial R-squared or partial Eta-squared); (6) calculate PRE from partial correlation, Cohen's f, or f_squared; (7) conduct a priori power analysis and plan the sample size for one or a set of predictors in regression analysis; (8) conduct post-hoc power analysis for one or a set of predictors in regression analysis with known sample size; (9) randomly pick numbers for Chinese Super Lotto and Double Color Balls; (10) assess course objective achievement in Outcome-Based Education.

r-kurt 1.1
Propagated dependencies: r-polynom@1.4-1 r-matrixcalc@1.0-6 r-labstatr@1.0.13 r-expm@1.0-0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=Kurt
Licenses: GPL 2+
Synopsis: Performs Kurtosis-Based Statistical Analyses
Description:

Computes measures of multivariate kurtosis, matrices of fourth-order moments and cumulants, kurtosis-based projection pursuit. Franceschini, C. and Loperfido, N. (2018, ISBN:978-3-319-73905-2). "An Algorithm for Finding Projections with Extreme Kurtosis". Loperfido, N. (2017,ISSN:0024-3795). "A New Kurtosis Matrix, with Statistical Applications".

r-kpcaig 1.0.1
Propagated dependencies: r-wallomicsdata@1.0 r-viridis@0.6.5 r-rgl@1.3.31 r-progress@1.2.3 r-kernlab@0.9-33 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kpcaIG
Licenses: GPL 3
Synopsis: Variables Interpretability with Kernel PCA
Description:

The kernelized version of principal component analysis (KPCA) has proven to be a valid nonlinear alternative for tackling the nonlinearity of biological sample spaces. However, it poses new challenges in terms of the interpretability of the original variables. kpcaIG aims to provide a tool to select the most relevant variables based on the kernel PCA representation of the data as in Briscik et al. (2023) <doi:10.1186/s12859-023-05404-y>. It also includes functions for 2D and 3D visualization of the original variables (as arrows) into the kernel principal components axes, highlighting the contribution of the most important ones.

r-keytoenglish 0.2.1
Propagated dependencies: r-stringr@1.6.0 r-openssl@2.3.4 r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/mcandocia/keyToEnglish
Licenses: GPL 2+
Synopsis: Convert Data to Memorable Phrases
Description:

Convert keys and other values to memorable phrases. Includes some methods to build lists of words.

r-kaphom 0.3
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kaphom
Licenses: GPL 3
Synopsis: Test the Homogeneity of Kappa Statistics
Description:

Tests the homogeneity of intraclass kappa statistics obtained from independent studies or a stratified study with binary results. It is desired to compare the kappa statistics obtained in multi-center studies or in a single stratified study to give a common or summary kappa using all available information. If the homogeneity test of these kappa statistics is not rejected, then it is possible to make inferences over a single kappa statistic that summarizes all the studies. Muammer Albayrak, Kemal Turhan, Yasemin Yavuz, Zeliha Aydin Kasap (2019) <doi:10.1080/03610918.2018.1538457> Jun-mo Nam (2003) <doi:10.1111/j.0006-341X.2003.00118.x> Jun-mo Nam (2005) <doi:10.1002/sim.2321>Mousumi Banerjee, Michelle Capozzoli, Laura McSweeney,Debajyoti Sinha (1999) <doi:10.2307/3315487> Allan Donner, Michael Eliasziw, Neil Klar (1996) <doi:10.2307/2533154>.

r-knockofftrio 1.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KnockoffTrio
Licenses: GPL 3
Synopsis: GWAS with Trio and Duo Data using Knockoff Statistics for FDR Control
Description:

Identification of putative causal variants in genome-wide association studies with trio and duo families. The package calculates the W feature statistics from KnockoffTrio and p-values from the family-based association test (FBAT) using trio and/or duo data. Compared to previous versions, a significant improvement has been made in Version 1.1.0 to allow the package to be applied not only to trio families but also to duo families. The package implements the methods in the paper: "Yang, Y., Wang, C., Liu, L., Buxbaum, J., He, Z., & Ionita-Laza, I. (2022). KnockoffTrio: A knockoff framework for the identification of putative causal variants in genome-wide association studies with trio design. The American Journal of Human Genetics, 109(10), 1761-1776.".

r-kequate 1.6.4
Propagated dependencies: r-mirt@1.45.1 r-ltm@1.2-0 r-equateirt@2.5.2
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kequate
Licenses: GPL 2 GPL 3
Synopsis: The Kernel Method of Test Equating
Description:

This package implements the kernel method of test equating as defined in von Davier, A. A., Holland, P. W. and Thayer, D. T. (2004) <doi:10.1007/b97446> and Andersson, B. and Wiberg, M. (2017) <doi:10.1007/s11336-016-9528-7> using the CB, EG, SG, NEAT CE/PSE and NEC designs, supporting Gaussian, logistic and uniform kernels and unsmoothed and pre-smoothed input data.

r-kerasnip 0.1.0
Propagated dependencies: r-tibble@3.3.0 r-rlang@1.1.6 r-reticulate@1.44.1 r-recipes@1.3.1 r-purrr@1.2.0 r-parsnip@1.3.3 r-keras3@1.4.0 r-dplyr@1.1.4 r-cli@3.6.5 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kerasnip
Licenses: Expat
Synopsis: Bridge Between 'keras' and 'tidymodels'
Description:

This package provides a seamless bridge between keras and the tidymodels frameworks. It allows for the dynamic creation of parsnip model specifications for keras models.

r-katex 1.5.0
Propagated dependencies: r-v8@8.0.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://docs.ropensci.org/katex/
Licenses: Expat
Synopsis: Rendering Math to HTML, 'MathML', or R-Documentation Format
Description:

Convert latex math expressions to HTML and MathML for use in markdown documents or package manual pages. The rendering is done in R using the V8 engine (i.e. server-side), which eliminates the need for embedding the MathJax library into your web pages. In addition a math-to-rd wrapper is provided to automatically render beautiful math in R documentation files.

r-kgschart 1.3.5
Propagated dependencies: r-stringr@1.6.0 r-shiny@1.11.1 r-png@0.1-8 r-nnet@7.3-20 r-matrixstats@1.5.0 r-magrittr@2.0.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-deepnet@0.2.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/kota7/kgschart
Licenses: Expat
Synopsis: KGS Rank Graph Parser
Description:

Restore underlining numeric data from rating history graph of KGS (an online platform of the game of go, <http://www.gokgs.com/>). A shiny application is also provided.

r-keyringr 0.4.0
Propagated dependencies: r-stringr@1.6.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=keyringr
Licenses: Expat
Synopsis: Decrypt Passwords from Gnome Keyring, Windows Data Protection API and macOS Keychain
Description:

Decrypts passwords stored in the Gnome Keyring, macOS Keychain and strings encrypted with the Windows Data Protection API.

r-kst 0.5-4
Propagated dependencies: r-sets@1.0-25 r-relations@0.6-15 r-proxy@0.4-27
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://homepage.uni-graz.at/en/cord.hockemeyer/
Licenses: GPL 2+
Synopsis: Knowledge Space Theory
Description:

Knowledge space theory by Doignon and Falmagne (1999) <doi:10.1007/978-3-642-58625-5> is a set- and order-theoretical framework, which proposes mathematical formalisms to operationalize knowledge structures in a particular domain. The kst package provides basic functionalities to generate, handle, and manipulate knowledge structures and knowledge spaces.

r-kseaapp 0.99.0
Propagated dependencies: r-gplots@3.2.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KSEAapp
Licenses: Expat
Synopsis: Kinase-Substrate Enrichment Analysis
Description:

This package infers relative kinase activity from phosphoproteomics data using the method described by Casado et al. (2013) <doi:10.1126/scisignal.2003573>.

r-kgraph 1.2.0
Propagated dependencies: r-shiny@1.11.1 r-sgraph@1.1.0 r-reshape2@1.4.5 r-rcolorbrewer@1.1-3 r-proc@1.19.0.1 r-plyr@1.8.9 r-opticskxi@1.2.1 r-magrittr@2.0.4 r-igraph@2.2.1 r-htmltools@0.5.8.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://gitlab.com/thomaschln/kgraph
Licenses: GPL 3
Synopsis: Knowledge Graphs Constructions and Visualizations
Description:

Knowledge graphs enable to efficiently visualize and gain insights into large-scale data analysis results, as p-values from multiple studies or embedding data matrices. The usual workflow is a user providing a data frame of association studies results and specifying target nodes, e.g. phenotypes, to visualize. The knowledge graph then shows all the features which are significantly associated with the phenotype, with the edges being proportional to the association scores. As the user adds several target nodes and grouping information about the nodes such as biological pathways, the construction of such graphs soon becomes complex. The kgraph package aims to enable users to easily build such knowledge graphs, and provides two main features: first, to enable building a knowledge graph based on a data frame of concepts relationships, be it p-values or cosine similarities; second, to enable determining an appropriate cut-off on cosine similarities from a complete embedding matrix, to enable the building of a knowledge graph directly from an embedding matrix. The kgraph package provides several display, layout and cut-off options, and has already proven useful to researchers to enable them to visualize large sets of p-value associations with various phenotypes, and to quickly be able to visualize embedding results. Two example datasets are provided to demonstrate these behaviors, and several live shiny applications are hosted by the CELEHS laboratory and Parse Health, as the KESER Mental Health application <https://keser-mental-health.parse-health.org/> based on Hong C. (2021) <doi:10.1038/s41746-021-00519-z>.

r-klar 1.7-3
Propagated dependencies: r-questionr@0.8.1 r-mass@7.3-65 r-combinat@0.0-8
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://statistik.tu-dortmund.de
Licenses: GPL 2 GPL 3
Synopsis: Classification and Visualization
Description:

Miscellaneous functions for classification and visualization, e.g. regularized discriminant analysis, sknn() kernel-density naive Bayes, an interface to svmlight and stepclass() wrapper variable selection for supervised classification, partimat() visualization of classification rules and shardsplot() of cluster results as well as kmodes() clustering for categorical data, corclust() variable clustering, variable extraction from different variable clustering models and weight of evidence preprocessing.

r-kuzur 0.2.3
Propagated dependencies: r-tidygraph@1.3.1 r-tibble@3.3.0 r-reticulate@1.44.1 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/WickM/kuzuR
Licenses: Expat
Synopsis: Interface to 'kuzu' Graph Database
Description:

This package provides a high-performance R interface to the kuzu graph database. It uses the reticulate package to wrap the official Python client ('kuzu', pandas', and networkx'), allowing users to interact with kuzu seamlessly from within R'. Key features include managing database connections, executing Cypher queries, and efficiently loading data from R data frames. It also provides seamless integration with the R ecosystem by converting query results directly into popular R data structures, including tibble', igraph', tidygraph', and g6R objects, making kuzu's powerful graph computation capabilities readily available for data analysis and visualization workflows in R'. The kuzu documentation can be found at <https://kuzudb.github.io/docs/>.

r-kfpls 1.0
Propagated dependencies: r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KFPLS
Licenses: GPL 3+
Synopsis: Kernel Functional Partial Least Squares
Description:

Implementation for kernel functional partial least squares (KFPLS) method. KFPLS method is developed for functional nonlinear models, and the method does not require strict constraints for the nonlinear structures. The crucial function of this package is KFPLS().

r-ktaucenters 1.0.0
Propagated dependencies: r-rcpp@1.1.0 r-mass@7.3-65 r-gse@4.2-3
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=ktaucenters
Licenses: GPL 2+
Synopsis: Robust Clustering Procedures
Description:

This package provides a clustering algorithm similar to K-Means is implemented, it has two main advantages, namely (a) The estimator is resistant to outliers, that means that results of estimator are still correct when there are atypical values in the sample and (b) The estimator is efficient, roughly speaking, if there are no outliers in the sample, results will be similar to those obtained by a classic algorithm (K-Means). Clustering procedure is carried out by minimizing the overall robust scale so-called tau scale. (see Gonzalez, Yohai and Zamar (2019) <arxiv:1906.08198>).

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