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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-kwcchangepoint 0.2.3
Propagated dependencies: r-tibble@3.3.0 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-fda-usc@2.2.0 r-ddalpha@1.3.16
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/adeeb99/KWCChangepoint
Licenses: Expat
Build system: r
Synopsis: Robust Changepoint Detection for Functional and Multivariate Data
Description:

Detect and test for changes in covariance structures of functional data, as well as changepoint detection for multivariate data more generally. Method for detecting non-stationarity in resting state functional Magnetic Resonance Imaging (fMRI) scans as seen in Ramsay, K., & Chenouri, S. (2025) <doi:10.1080/10485252.2025.2503891> is implemented in fmri_changepoints(). Also includes depth- and rank-based implementation of the wild binary segmentation algorithm for detecting multiple changepoints in multivariate data.

r-kfigr 1.2.1
Propagated dependencies: r-knitr@1.50
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/mkoohafkan/kfigr
Licenses: GPL 3+
Build system: r
Synopsis: Integrated Code Chunk Anchoring and Referencing for R Markdown Documents
Description:

This package provides a streamlined cross-referencing system for R Markdown documents generated with knitr'. R Markdown is an authoring format for generating dynamic content from R. kfigr provides a hook for anchoring code chunks and a function to cross-reference document elements generated from said chunks, e.g. figures and tables.

r-kgode 1.0.5
Propagated dependencies: r-r6@2.6.1 r-pspline@1.0-21 r-pracma@2.4.6 r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KGode
Licenses: GPL 2+
Build system: r
Synopsis: Kernel Based Gradient Matching for Parameter Inference in Ordinary Differential Equations
Description:

The kernel ridge regression and the gradient matching algorithm proposed in Niu et al. (2016) <https://proceedings.mlr.press/v48/niu16.html> and the warping algorithm proposed in Niu et al. (2017) <DOI:10.1007/s00180-017-0753-z> are implemented for parameter inference in differential equations. Four schemes are provided for improving parameter estimation in odes by using the odes regularisation and warping.

r-kcsknnshiny 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-rhandsontable@0.3.8 r-fnn@1.1.4.1 r-dplyr@1.1.4 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KCSKNNShiny
Licenses: GPL 2
Build system: r
Synopsis: K-Nearest Neighbour Classifier
Description:

It predicts any attribute (categorical) given a set of input numeric predictor values. Note that only numeric input predictors should be given. The k value can be chosen according to accuracies provided. The attribute to be predicted can be selected from the dropdown provided (select categorical attribute). This is because categorical attributes cannot be given as inputs here. A handsontable is also provided to enter the input predictor values.

r-kantorovich 3.2.0
Dependencies: gmp@6.3.0
Propagated dependencies: r-slam@0.1-55 r-roi-plugin-glpk@1.0-0 r-rglpk@0.6-5.1 r-rcdd@1.6 r-ompr-roi@1.0.2 r-ompr@1.0.4 r-lpsolve@5.6.23 r-gmp@0.7-5 r-cvxr@1.0-15
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/stla/kantorovich
Licenses: GPL 3
Build system: r
Synopsis: Kantorovich Distance Between Probability Measures
Description:

Computes the Kantorovich distance between two probability measures on a finite set. The Kantorovich distance is also known as the Monge-Kantorovich distance or the first Wasserstein distance.

r-karlen 0.0.2
Propagated dependencies: r-tibble@3.3.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://rmagno.eu/karlen/
Licenses: FSDG-compatible
Build system: r
Synopsis: Real-Time PCR Data Sets by Karlen et al. (2007)
Description:

Real-time quantitative polymerase chain reaction (qPCR) data sets by Karlen et al. (2007) <doi:10.1186/1471-2105-8-131>. Provides one single tabular tidy data set in long format, encompassing 32 dilution series, for seven PCR targets and four biological samples. The targeted amplicons are within the murine genes: Cav1, Ccn2, Eln, Fn1, Rpl27, Hspg2, and Serpine1, respectively. Dilution series: scheme 1 (Cav1, Eln, Hspg2, Serpine1): 1-fold, 10-fold, 50-fold, and 100-fold; scheme 2 (Ccn2, Rpl27, Fn1): 1-fold, 10-fold, 50-fold, 100-fold and 1000-fold. For each concentration there are five replicates, except for the 1000-fold concentration, where only two replicates were performed. Each amplification curve is 40 cycles long. Original raw data file is Additional file 2 from "Statistical significance of quantitative PCR" by Y. Karlen, A. McNair, S. Perseguers, C. Mazza, and N. Mermod (2007) <https://static-content.springer.com/esm/art%3A10.1186%2F1471-2105-8-131/MediaObjects/12859_2006_1503_MOESM2_ESM.ZIP>.

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+
Build system: r
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-ktensorgraphs 1.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KTensorGraphs
Licenses: GPL 2+
Build system: r
Synopsis: Co-Tucker3 Analysis of Two Sequences of Matrices
Description:

This package provides a function called COTUCKER3() (Co-Inertia Analysis + Tucker3 method) which performs a Co-Tucker3 analysis of two sequences of matrices, as well as other functions called PCA() (Principal Component Analysis) and BGA() (Between-Groups Analysis), which perform analysis of one matrix, COIA() (Co-Inertia Analysis), which performs analysis of two matrices, PTA() (Partial Triadic Analysis), STATIS(), STATISDUAL() and TUCKER3(), which perform analysis of a sequence of matrices, and BGCOIA() (Between-Groups Co-Inertia Analysis), STATICO() (STATIS method + Co-Inertia Analysis), COSTATIS() (Co-Inertia Analysis + STATIS method), which also perform analysis of two sequences of matrices.

r-kstmatrix 2.2-1
Propagated dependencies: r-tidyr@1.3.1 r-sets@1.0-25 r-rsvg@2.7.0 r-pks@0.6-1 r-diagrammersvg@0.1 r-diagrammer@1.0.11
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kstMatrix
Licenses: GPL 3
Build system: r
Synopsis: Basic Functions in Knowledge Space Theory Using Matrix Representation
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 kstMatrix package provides basic functionalities to generate, handle, and manipulate knowledge structures and knowledge spaces. Opposed to the kst package, kstMatrix uses matrix representations for knowledge structures. Furthermore, kstMatrix contains several knowledge spaces developed by the research group around Cornelia Dowling through querying experts.

r-knitxl 0.1.0
Propagated dependencies: r-yaml@2.3.10 r-xml2@1.5.0 r-stringr@1.6.0 r-readr@2.1.6 r-readbitmap@0.1.5 r-r6@2.6.1 r-purrr@1.2.0 r-openxlsx@4.2.8.1 r-magrittr@2.0.4 r-knitr@1.50 r-glue@1.8.0 r-commonmark@2.0.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/dreanod/knitxl
Licenses: GPL 3+
Build system: r
Synopsis: Generates a Spreadsheet Report from an 'rmarkdown' File
Description:

Convert an R Markdown documents into an .xlsx spreadsheet reports with the knitxl() function, which works similarly to knit() from the knitr package. The generated report can be opened in Excel or similar software for further analysis and presentation.

r-klink 1.1.0
Propagated dependencies: r-xml2@1.5.0 r-verbalisr@0.7.2 r-shinyjs@2.1.0 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-pedtools@2.10.0 r-pedprobr@1.0.1 r-pedmut@0.9.0 r-pedfamilias@0.2.4 r-openxlsx@4.2.8.1 r-norstr@0.2.1 r-gt@1.3.0 r-forrel@1.8.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/magnusdv/KLINK
Licenses: GPL 3+
Build system: r
Synopsis: Kinship Analysis with Linked Markers
Description:

This package provides a shiny application for forensic kinship testing, based on the pedsuite R packages. KLINK is closely aligned with the (non-R) software Familias and FamLink', but offers several unique features, including visualisations and automated report generation. The calculation of likelihood ratios supports pairs of linked markers, and all common mutation models.

r-kscorrect 1.4.0
Propagated dependencies: r-mclust@6.1.2 r-mass@7.3-65 r-iterators@1.0.14 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/pnovack-gottshall/KScorrect
Licenses: CC0
Build system: r
Synopsis: Lilliefors-Corrected Kolmogorov-Smirnov Goodness-of-Fit Tests
Description:

This package implements the Lilliefors-corrected Kolmogorov-Smirnov test for use in goodness-of-fit tests, suitable when population parameters are unknown and must be estimated by sample statistics. P-values are estimated by simulation. Can be used with a variety of continuous distributions, including normal, lognormal, univariate mixtures of normals, uniform, loguniform, exponential, gamma, and Weibull distributions. Functions to generate random numbers and calculate density, distribution, and quantile functions are provided for use with the log uniform and mixture distributions.

r-knockoff 0.3.6
Propagated dependencies: r-rspectra@0.16-2 r-rdsdp@1.0.6 r-matrix@1.7-4 r-gtools@3.9.5 r-glmnet@4.1-10 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://web.stanford.edu/group/candes/knockoffs/index.html
Licenses: GPL 3
Build system: r
Synopsis: The Knockoff Filter for Controlled Variable Selection
Description:

The knockoff filter is a general procedure for controlling the false discovery rate (FDR) when performing variable selection. For more information, see the website below and the accompanying paper: Candes et al., "Panning for gold: model-X knockoffs for high-dimensional controlled variable selection", J. R. Statist. Soc. B (2018) 80, 3, pp. 551-577.

r-kernelknn 1.1.6
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://github.com/mlampros/KernelKnn
Licenses: Expat
Build system: r
Synopsis: Kernel k Nearest Neighbors
Description:

Extends the simple k-nearest neighbors algorithm by incorporating numerous kernel functions and a variety of distance metrics. The package takes advantage of RcppArmadillo to speed up the calculation of distances between observations.

r-kuzco 0.1.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-ollamar@1.2.2 r-magick@2.9.0 r-jsonlite@2.0.0 r-imager@1.0.5 r-gtextras@0.6.2 r-gt@1.3.0 r-ellmer@0.4.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://frankiethull.github.io/kuzco/
Licenses: Expat
Build system: r
Synopsis: Computer Vision with Large Language Models
Description:

Make computer vision tasks approachable in R by leveraging Large Language Models. Providing fine-tuned prompts, boilerplate functions, and input/output helpers for common computer vision workflows, such as classifying and describing images. Functions are designed to take images as input and return structured data, helping users build practical applications with minimal code.

r-kza 4.1.0.1
Dependencies: fftw@3.3.10
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kza
Licenses: GPL 3
Build system: r
Synopsis: Kolmogorov-Zurbenko Adaptive Filters
Description:

Time Series Analysis including break detection, spectral analysis, KZ Fourier Transforms.

r-kfas 1.6.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/helske/KFAS
Licenses: GPL 2+
Build system: r
Synopsis: Kalman Filter and Smoother for Exponential Family State Space Models
Description:

State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.

r-kanjistat 0.14.2
Propagated dependencies: r-xml2@1.5.0 r-transport@0.15-4 r-sysfonts@0.8.9 r-stringr@1.6.0 r-stringi@1.8.7 r-showtext@0.9-7 r-roi@1.0-1 r-rlang@1.1.6 r-rcpp@1.1.0 r-rann@2.6.2 r-purrr@1.2.0 r-png@0.1-8 r-matrix@1.7-4 r-lifecycle@1.0.4 r-gsubfn@0.7 r-dendextend@1.19.1 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://dschuhmacher.github.io/kanjistat/
Licenses: GPL 3+
Build system: r
Synopsis: Statistical Framework for the Analysis of Japanese Kanji Characters
Description:

Various tools and data sets that support the study of kanji, including their morphology, decomposition and concepts of distance and similarity between them.

r-k5 0.2.1
Propagated dependencies: r-usethis@3.2.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-glue@1.8.0 r-ggplot2@4.0.1 r-fs@1.6.6 r-dplyr@1.1.4 r-clipr@0.8.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://k5cents.github.io/k5/
Licenses: GPL 3
Build system: r
Synopsis: Kiernan Nicholls Miscellaneous
Description:

Quality of life functions for interactive programming. Shortcuts for common combinations of functions or different default arguments. Not to be used in production level scripts, but useful for exploring and quickly manipulating data for easy analysis. Also imports a variety of packages to facilitate the installation of those imported packages on the host machine.

r-kraljicmatrix 0.2.1
Propagated dependencies: r-tibble@3.3.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/koalaverse/KraljicMatrix
Licenses: Expat
Build system: r
Synopsis: Quantified Implementation of the Kraljic Matrix
Description:

This package implements a quantified approach to the Kraljic Matrix (Kraljic, 1983, <https://hbr.org/1983/09/purchasing-must-become-supply-management>) for strategically analyzing a firmâ s purchasing portfolio. It combines multi-objective decision analysis to measure purchasing characteristics and uses this information to place products and services within the Kraljic Matrix.

r-kimisc 1.0.1
Propagated dependencies: r-plyr@1.8.9 r-memoise@2.0.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://krlmlr.github.io/kimisc/
Licenses: Expat
Build system: r
Synopsis: Kirill's Miscellaneous Functions
Description:

This package provides a collection of useful functions not found anywhere else, mainly for programming: Pretty intervals, generalized lagged differences, checking containment in an interval, and an alternative interface to assign().

r-kertests 0.1.4
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kerTests
Licenses: GPL 2+
Build system: r
Synopsis: Generalized Kernel Two-Sample Tests
Description:

New kernel-based test and fast tests for testing whether two samples are from the same distribution. They work well particularly for high-dimensional data. Song, H. and Chen, H. (2023) <arXiv:2011.06127>.

r-kdml 1.1.1
Propagated dependencies: r-np@0.60-18 r-mass@7.3-65 r-markdown@2.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kdml
Licenses: GPL 2+
Build system: r
Synopsis: Kernel Distance Metric Learning for Mixed-Type Data
Description:

Distance metrics for mixed-type data consisting of continuous, nominal, and ordinal variables. This methodology uses additive and product kernels to calculate similarity functions and metrics, and selects variables relevant to the underlying distance through bandwidth selection via maximum similarity cross-validation. These methods can be used in any distance-based algorithm, such as distance-based clustering. For further details, we refer the reader to Ghashti and Thompson (2024) <doi:10.1007/s00357-024-09493-z> for dkps() methodology, and Ghashti (2024) <doi:10.14288/1.0443975> for dkss() methodology.

r-kmunicate 0.2.5
Propagated dependencies: r-tidyr@1.3.1 r-survival@3.8-3 r-pammtools@0.7.3 r-ggplot2@4.0.1 r-cowplot@1.2.0 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://ellessenne.github.io/KMunicate-package/
Licenses: Expat
Build system: r
Synopsis: KMunicate-Style Kaplan–Meier Plots
Description:

Produce Kaplanâ Meier plots in the style recommended following the KMunicate study by Morris et al. (2019) <doi:10.1136/bmjopen-2019-030215>. The KMunicate style consists of Kaplan-Meier curves with confidence intervals to quantify uncertainty and an extended risk table (per treatment arm) depicting the number of study subjects at risk, events, and censored observations over time. The resulting plots are built using ggplot2 and can be further customised to a certain extent, including themes, fonts, and colour scales.

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Total results: 68658