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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-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
Build system: r
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-kmblock 0.1.4
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-foreach@1.5.2 r-dorng@1.8.6.2 r-doparallel@1.0.17 r-blockmodeling@1.1.8
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kmBlock
Licenses: GPL 2+
Build system: r
Synopsis: k-Means Like Blockmodeling of One-Mode and Linked Networks
Description:

This package implements k-means like blockmodeling of one-mode and linked networks as presented in Žiberna (2020) <doi:10.1016/j.socnet.2019.10.006>. The development of this package is financially supported by the Slovenian Research Agency (<https://www.arrs.si/>) within the research programs P5-0168 and the research projects J7-8279 (Blockmodeling multilevel and temporal networks) and J5-2557 (Comparison and evaluation of different approaches to blockmodeling dynamic networks by simulations with application to Slovenian co-authorship networks).

r-kofm 1.1.1
Propagated dependencies: r-tensormiss@1.1.1 r-rspectra@0.16-2 r-mefm@0.1.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KOFM
Licenses: GPL 3
Build system: r
Synopsis: Test the Kronecker Product Structure in Tensor Factor Models
Description:

To test if a tensor time series following a Tucker-decomposition factor model has a Kronecker product structure. Supplementary functions for tensor reshape and its reversal are also included.

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-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
Build system: r
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-kriens 0.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: http://www.alephdue.com
Licenses: Modified BSD
Build system: r
Synopsis: Continuation Passing Style Development
Description:

This package provides basic functions for Continuation-Passing Style development.

r-kangar00 1.4.2
Propagated dependencies: r-sqldf@0.4-11 r-lattice@0.22-7 r-igraph@2.2.1 r-data-table@1.17.8 r-compquadform@1.4.4 r-bigmemory@4.6.4
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://kangar00.manitz.org/
Licenses: GPL 2
Build system: r
Synopsis: Kernel Approaches for Nonlinear Genetic Association Regression
Description:

This package provides methods to extract information on pathways, genes and various single-nucleotid polymorphisms (SNPs) from online databases. It provides functions for data preparation and evaluation of genetic influence on a binary outcome using the logistic kernel machine test (LKMT). Three different kernel functions are offered to analyze genotype information in this variance component test: A linear kernel, a size-adjusted kernel and a network-based kernel).

r-krm 2022.10-17
Propagated dependencies: r-kyotil@2024.11-01
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=krm
Licenses: GPL 2
Build system: r
Synopsis: Kernel Based Regression Models
Description:

This package implements several methods for testing the variance component parameter in regression models that contain kernel-based random effects, including a maximum of adjusted scores test. Several kernels are supported, including a profile hidden Markov model mutual information kernel for protein sequence. This package is described in Fong et al. (2015) <DOI:10.1093/biostatistics/kxu056>.

r-kogmwu 1.2
Propagated dependencies: r-pheatmap@1.0.13
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KOGMWU
Licenses: GPL 3
Build system: r
Synopsis: Functional Summary and Meta-Analysis of Gene Expression Data
Description:

Rank-based tests for enrichment of KOG (euKaryotic Orthologous Groups) classes with up- or down-regulated genes based on a continuous measure. The meta-analysis is based on correlation of KOG delta-ranks across datasets (delta-rank is the difference between mean rank of genes belonging to a KOG class and mean rank of all other genes). With binary measure (1 or 0 to indicate significant and non-significant genes), one-tailed Fisher's exact test for over-representation of each KOG class among significant genes will be performed.

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
Build system: r
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-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
Build system: r
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-karsts 2.4.1
Propagated dependencies: r-zoo@1.8-14 r-tserieschaos@0.1-13.1 r-tseries@0.10-58 r-tcltk2@1.6.1 r-stlplus@0.5.1 r-stinepack@1.5 r-rgl@1.3.31 r-plot3d@1.4.2 r-nonlineartseries@0.3.1 r-mvn@6.3 r-missforest@1.6.1 r-mgcv@1.9-4 r-infotheo@1.2.0.1 r-forecast@8.24.0 r-circular@0.5-2
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KarsTS
Licenses: GPL 2+
Build system: r
Synopsis: An Interface for Microclimate Time Series Analysis
Description:

An R code with a GUI for microclimate time series, with an emphasis on underground environments. KarsTS provides linear and nonlinear methods, including recurrence analysis (Marwan et al. (2007) <doi:10.1016/j.physrep.2006.11.001>) and filling methods (Moffat et al. (2007) <doi:10.1016/j.agrformet.2007.08.011>), as well as tools to manipulate easily time series and gap sets.

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
Build system: r
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-kitagawa 3.1.3
Propagated dependencies: r-psd@2.1.2 r-kelvin@2.0-3 r-bessel@0.7-0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/abarbour/kitagawa
Licenses: GPL 2+
Build system: r
Synopsis: Spectral Response of Water Wells to Harmonic Strain and Pressure Signals
Description:

This package provides tools to calculate the theoretical hydrodynamic response of an aquifer undergoing harmonic straining or pressurization, or analyze measured responses. There are two classes of models here, designed for use with confined aquifers: (1) for sealed wells, based on the model of Kitagawa et al (2011, <doi:10.1029/2010JB007794>), and (2) for open wells, based on the models of Cooper et al (1965, <doi:10.1029/JZ070i016p03915>), Hsieh et al (1987, <doi:10.1029/WR023i010p01824>), Rojstaczer (1988, <doi:10.1029/JB093iB11p13619>), Liu et al (1989, <doi:10.1029/JB094iB07p09453>), and Wang et al (2018, <doi:10.1029/2018WR022793>). Wang's solution is a special exception which allows for leakage out of the aquifer (semi-confined); it is equivalent to Hsieh's model when there is no leakage (the confined case). These models treat strain (or aquifer head) as an input to the physical system, and fluid-pressure (or water height) as the output. The applicable frequency band of these models is characteristic of seismic waves, atmospheric pressure fluctuations, and solid earth tides.

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@1.3.0 r-dimensio@0.14.1 r-config@0.3.2 r-bslib@0.9.0 r-arkhe@1.11.0 r-aion@1.7.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://codeberg.org/tesselle/kinesis
Licenses: GPL 3+
Build system: r
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-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@1.5.0 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
Build system: r
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-kernscr 1.0.7
Propagated dependencies: r-mvtnorm@1.3-3 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: http://borishejblum.github.io/kernscr/
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: Kernel Machine Score Test for Semi-Competing Risks
Description:

Kernel Machine Score Test for Pathway Analysis in the Presence of Semi-Competing Risks. Method is detailed in: Neykov, Hejblum & Sinnott (2018) <doi: 10.1177/0962280216653427>.

r-klassr 1.0.4
Propagated dependencies: r-tm@0.7-16 r-jsonlite@2.0.0 r-igraph@2.2.1 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://statisticsnorway.github.io/ssb-klassr/
Licenses: Expat
Build system: r
Synopsis: Classifications for Statistics Norway
Description:

This package provides functions to search, retrieve, apply and update classification standards and code lists using Statistics Norway's API <https://www.ssb.no/klass> from the system KLASS'. Retrieves classifications by date with options to choose language, hierarchical level and formatting.

r-kissmig 2.0-1
Propagated dependencies: r-terra@1.8-86 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://purl.oclc.org/wsl/kissmig
Licenses: GPL 3+
Build system: r
Synopsis: a Keep It Simple Species Migration Model
Description:

Simulating species migration and range dynamics under stable or changing environmental conditions based on a simple, raster-based, deterministic or stochastic migration model. KISSMig runs on binary or quantitative suitability maps, which are pre-calculated with niche-based habitat suitability models (also called ecological niche models (ENMs) or species distribution models (SDMs)). Nobis & Normand (2014), <doi:10.1111/ecog.00930>.

r-kosel 0.0.1
Propagated dependencies: r-ordinalnet@2.13 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://arxiv.org/pdf/1907.03153.pdf
Licenses: GPL 3
Build system: r
Synopsis: Variable Selection by Revisited Knockoffs Procedures
Description:

This package performs variable selection for many types of L1-regularised regressions using the revisited knockoffs procedure. This procedure uses a matrix of knockoffs of the covariates independent from the response variable Y. The idea is to determine if a covariate belongs to the model depending on whether it enters the model before or after its knockoff. The procedure suits for a wide range of regressions with various types of response variables. Regression models available are exported from the R packages glmnet and ordinalNet'. Based on the paper linked to via the URL below: Gegout A., Gueudin A., Karmann C. (2019) <arXiv:1907.03153>.

r-kkmeans 0.1.3
Propagated dependencies: 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=kkmeans
Licenses: GPL 3
Build system: r
Synopsis: Fast Implementations of Kernel K-Means
Description:

Implementations several algorithms for kernel k-means. The default OTQT algorithm is a fast alternative to standard implementations of kernel k-means, particularly in cases with many clusters. For a small number of clusters, the implemented MacQueen method typically performs the fastest. For more details and performance evaluations, see Berlinski and Maitra (2025) <doi:10.1002/sam.70032>.

r-kerdaa 0.1.1
Propagated dependencies: 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=kerDAA
Licenses: GPL 2+
Build system: r
Synopsis: New Kernel-Based Test for Differential Association Analysis
Description:

This package provides a new practical method to evaluate whether relationships between two sets of high-dimensional variables are different or not across two conditions. Song, H. and Wu, M.C. (2023) <arXiv:2307.15268>.

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-kgrams 0.2.1
Propagated dependencies: r-rlang@1.1.6 r-rdpack@2.6.4 r-rcppprogress@0.4.2 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://vgherard.github.io/kgrams/
Licenses: GPL 3+
Build system: r
Synopsis: Classical k-gram Language Models
Description:

Training and evaluating k-gram language models in R, supporting several probability smoothing techniques, perplexity computations, random text generation and more.

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