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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-longpower 1.0.27
Propagated dependencies: r-nlme@3.1-168 r-lme4@1.1-37
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/mcdonohue/longpower
Licenses: GPL 2+
Build system: r
Synopsis: Sample Size Calculations for Longitudinal Data
Description:

Compute power and sample size for linear models of longitudinal data. Supported models include mixed-effects models and models fit by generalized least squares and generalized estimating equations. The package is described in Iddi and Donohue (2022) <DOI:10.32614/RJ-2022-022>. Relevant formulas are derived by Liu and Liang (1997) <DOI:10.2307/2533554>, Diggle et al (2002) <ISBN:9780199676750>, and Lu, Luo, and Chen (2008) <DOI:10.2202/1557-4679.1098>.

r-lopart 2024.6.19
Propagated dependencies: r-rcpp@1.1.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/tdhock/LOPART
Licenses: GPL 3
Build system: r
Synopsis: Labeled Optimal Partitioning
Description:

Change-point detection algorithm with label constraints and a penalty for each change outside of labels. Read TD Hocking, A Srivastava (2023) <doi:10.1007/s00180-022-01238-z> for details.

r-lowpassfilter 1.0-2
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=lowpassFilter
Licenses: GPL 3
Build system: r
Synopsis: Lowpass Filtering
Description:

This package creates lowpass filters which are commonly used in ion channel recordings. It supports generation of random numbers that are filtered, i.e. follow a model for ion channel recordings, see <doi:10.1109/TNB.2018.2845126>. Furthermore, time continuous convolutions of piecewise constant signals with the kernel of lowpass filters can be computed.

r-lidartree 4.0.8
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-reldist@1.7-2 r-lidr@4.2.3 r-leaps@3.2 r-imager@1.0.5 r-gvlma@1.0.0.3 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://lidar.pages.mia.inra.fr/lidaRtRee/
Licenses: GPL 3
Build system: r
Synopsis: Forest Analysis with Airborne Laser Scanning (LiDAR) Data
Description:

This package provides functions for forest objects detection, structure metrics computation, model calibration and mapping with airborne laser scanning: co-registration of field plots (Monnet and Mermin (2014) <doi:10.3390/f5092307>); tree detection (method 1 in Eysn et al. (2015) <doi:10.3390/f6051721>) and segmentation; forest parameters estimation with the area-based approach: model calibration with ground reference, and maps export (Aussenac et al. (2023) <doi:10.12688/openreseurope.15373.2>); extraction of both physical (gaps, edges, trees) and statistical features useful for e.g. habitat suitability modeling (Glad et al. (2020) <doi:10.1002/rse2.117>) and forest maturity mapping (Fuhr et al. (2022) <doi:10.1002/rse2.274>).

r-languager 1.6
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=languageR
Licenses: GPL 2+
Build system: r
Synopsis: Data Sets and Functions with Analyzing Linguistic Data: A Practical Introduction to Statistics
Description:

Data sets exemplifying statistical methods, and some facilitatory utility functions used in ``Analyzing Linguistic Data: A practical introduction to statistics using R'', Cambridge University Press, 2008.

r-lmm 1.4
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/jinghuazhao/R
Licenses: FSDG-compatible
Build system: r
Synopsis: Linear Mixed Models
Description:

It implements Expectation/Conditional Maximization Either (ECME) and rapidly converging algorithms as well as Bayesian inference for linear mixed models, which is described in Schafer, J.L. (1998) "Some improved procedures for linear mixed models". Dept. of Statistics, The Pennsylvania State University.

r-lilikoi 2.1.1
Propagated dependencies: r-survminer@0.5.1 r-survival@3.8-3 r-stringr@1.6.0 r-scales@1.4.0 r-rweka@0.4-46 r-reticulate@1.44.1 r-reshape@0.8.10 r-rcy3@2.30.0 r-proc@1.19.0.1 r-princurve@2.1.6 r-preprocesscore@1.72.0 r-plyr@1.8.9 r-pathview@1.50.0 r-mlmetrics@1.1.3 r-metrics@0.1.4 r-m3c@1.32.0 r-limma@3.66.0 r-infotheo@1.2.0.1 r-impute@1.84.0 r-h2o@3.44.0.3 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-gbm@2.2.2 r-dplyr@1.1.4 r-caret@7.0-1 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=lilikoi
Licenses: GPL 2
Build system: r
Synopsis: Metabolomics Personalized Pathway Analysis Tool
Description:

This package provides a comprehensive analysis tool for metabolomics data. It consists a variety of functional modules, including several new modules: a pre-processing module for normalization and imputation, an exploratory data analysis module for dimension reduction and source of variation analysis, a classification module with the new deep-learning method and other machine-learning methods, a prognosis module with cox-PH and neural-network based Cox-nnet methods, and pathway analysis module to visualize the pathway and interpret metabolite-pathway relationships. References: H. Paul Benton <http://www.metabolomics-forum.com/index.php?topic=281.0> Jeff Xia <https://github.com/cangfengzhe/Metabo/blob/master/MetaboAnalyst/website/name_match.R> Travers Ching, Xun Zhu, Lana X. Garmire (2018) <doi:10.1371/journal.pcbi.1006076>.

r-lfproqc 1.4.1
Propagated dependencies: r-vsn@3.78.0 r-vim@6.2.6 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-reshape2@1.4.5 r-reshape@0.8.10 r-plotly@4.11.0 r-pcamethods@2.2.0 r-matrixstats@1.5.0 r-mass@7.3-65 r-magrittr@2.0.4 r-limma@3.66.0 r-laeken@0.5.3 r-hmisc@5.2-4 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/kabilansbio/lfproQC
Licenses: GPL 3
Build system: r
Synopsis: Quality Control for Label-Free Proteomics Expression Data
Description:

Label-free bottom-up proteomics expression data is often affected by data heterogeneity and missing values. Normalization and missing value imputation are commonly used techniques to address these issues and make the dataset suitable for further downstream analysis. This package provides an optimal combination of normalization and imputation methods for the dataset. The package utilizes three normalization methods and three imputation methods.The statistical evaluation measures named pooled co-efficient of variance, pooled estimate of variance and pooled median absolute deviation are used for selecting the best combination of normalization and imputation method for the given dataset. The user can also visualize the results by using various plots available in this package. The user can also perform the differential expression analysis between two sample groups with the function included in this package. The chosen three normalization methods, three imputation methods and three evaluation measures were chosen for this study based on the research papers published by Välikangas et al. (2016) <doi:10.1093/bib/bbw095>, Jin et al. (2021) <doi:10.1038/s41598-021-81279-4> and Srivastava et al. (2023) <doi:10.2174/1574893618666230223150253>.This work has published by Sakthivel et al. (2025) <doi:10.1021/acs.jproteome.4c00552>.

r-lock5data 4.0.1
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=Lock5Data
Licenses: GPL 2
Build system: r
Synopsis: Datasets for "Statistics: UnLocking the Power of Data"
Description:

Datasets for the fourth edition of "Statistics: Unlocking the Power of Data" by Lock^5 Includes versions of datasets from earlier editions.

r-logregequiv 0.1.5
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=LogRegEquiv
Licenses: Expat
Build system: r
Synopsis: Logistic Regression Equivalence
Description:

This package provides tools for assessing equivalence of similar Logistic Regression models.

r-likelihoodtools 1.0.0
Propagated dependencies: r-rlang@1.1.6 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/ajpelu/likelihoodTools
Licenses: GPL 3+
Build system: r
Synopsis: Managing Results from Maximum Likelihood Estimation
Description:

Managing and exploring parameter estimation results derived from Maximum Likelihood Estimation (MLE) using the likelihood package. It provides functions for organizing, visualizing, and summarizing MLE outcomes, streamlining statistical analysis workflows. By improving interpretation and facilitating model evaluation, it helps users gain deeper insights into parameter estimation and model fitting, making MLE result exploration more efficient and accessible. See Goffe et al. (1994) <doi:10.1016/0304-4076(94)90038-8> for details on MLE, and Canham and Uriarte (2006) <doi:10.1890/04-0657> for application of MLE using likelihood'.

r-lcmsqa 1.0.2
Propagated dependencies: r-shinywidgets@0.9.0 r-shinyjs@2.1.0 r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-plotly@4.11.0 r-ggplot2@4.0.1 r-dt@0.34.0 r-data-table@1.17.8 r-bsplus@0.1.5
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=LCMSQA
Licenses: GPL 3+
Build system: r
Synopsis: Liquid Chromatography/Mass Spectrometry (LC/MS) Quality Assessment
Description:

The goal of LCMSQA is to make it easy to check the quality of liquid chromatograph/mass spectrometry (LC/MS) experiments using a shiny application. This package provides interactive data visualizations for quality control (QC) samples, including total ion current chromatogram (TIC), base peak chromatogram (BPC), mass spectrum, extracted ion chromatogram (XIC), and feature detection results from internal standards or known metabolites.

r-lotri 1.0.2
Propagated dependencies: r-crayon@1.5.3 r-cpp11armadillo@0.5.4 r-cpp11@0.5.2 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://nlmixr2.github.io/lotri/
Licenses: GPL 2+
Build system: r
Synopsis: Simple Way to Specify Symmetric, Block Diagonal Matrices
Description:

This package provides a simple mechanism to specify a symmetric block diagonal matrices (often used for covariance matrices). This is based on the domain specific language implemented in nlmixr2 but expanded to create matrices in R generally instead of specifying parts of matrices to estimate. It has expanded to include some matrix manipulation functions that are generally useful for rxode2 and nlmixr2'.

r-longmemo 1.1-4
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=longmemo
Licenses: GPL 2+
Build system: r
Synopsis: Statistics for Long-Memory Processes (Book Jan Beran), and Related Functionality
Description:

Datasets and Functionality from Jan Beran (1994). Statistics for Long-Memory Processes; Chapman & Hall. Estimation of Hurst (and more) parameters for fractional Gaussian noise, fARIMA and FEXP models.

r-lilrhino 1.2.2
Propagated dependencies: r-tm@0.7-16 r-stringi@1.8.7 r-snowballc@0.7.1 r-readr@2.1.6 r-neuralnet@1.44.2 r-keras@2.16.0 r-ggplot2@4.0.1 r-fnn@1.1.4.1 r-fastmatch@1.1-6 r-e1071@1.7-16 r-dplyr@1.1.4 r-data-table@1.17.8 r-beepr@2.0
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=LilRhino
Licenses: GPL 2
Build system: r
Synopsis: For Implementation of Feed Reduction, Learning Examples, NLP and Code Management
Description:

This is for code management functions, NLP tools, a Monty Hall simulator, and for implementing my own variable reduction technique called Feed Reduction. The Feed Reduction technique is not yet published, but is merely a tool for implementing a series of binary neural networks meant for reducing data into N dimensions, where N is the number of possible values of the response variable.

r-lsebootls 0.1.0
Propagated dependencies: r-tibble@3.3.0 r-rlecuyer@0.3-8 r-lsts@2.1 r-iterators@1.0.14 r-foreach@1.5.2 r-dorng@1.8.6.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=LSEbootLS
Licenses: GPL 3+
Build system: r
Synopsis: Bootstrap Methods for Regression Models with Locally Stationary Errors
Description:

This package implements bootstrap methods for linear regression models with errors following a time-varying process, focusing on approximating the distribution of the least-squares estimator for regression models with locally stationary errors. It enables the construction of bootstrap and classical confidence intervals for regression coefficients, leveraging intensive simulation studies and real data analysis.

r-lue 0.2.1
Propagated dependencies: r-raster@3.6-32 r-ncdf4@1.24
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=lue
Licenses: GPL 2
Build system: r
Synopsis: Light Use Efficiency Model to Estimate Biomass and YIELD with and Without Vapour Pressure Deficit
Description:

This package contains LUE_BIOMASS(),LUE_BIOMASS_VPD(), LUE_YIELD() and LUE_YIELD_VPD() to estimate aboveground biomass and crop yield firstly by calculating the Absorbed Photosynthetically Active Radiation (APAR) and secondly the actual values of light use efficiency with and without vapour presure deficit Shi et al.(2007) <doi:10.2134/agronj2006.0260>.

r-longevity 1.3
Propagated dependencies: r-rsolnp@2.0.1 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-numderiv@2016.8-1.1
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://lbelzile.github.io/longevity/
Licenses: GPL 3
Build system: r
Synopsis: Statistical Methods for the Analysis of Excess Lifetimes
Description:

This package provides a collection of parametric and nonparametric methods for the analysis of survival data. Parametric families implemented include Gompertz-Makeham, exponential and generalized Pareto models and extended models. The package includes an implementation of the nonparametric maximum likelihood estimator for arbitrary truncation and censoring pattern based on Turnbull (1976) <doi:10.1111/j.2517-6161.1976.tb01597.x>, along with graphical goodness-of-fit diagnostics. Parametric models for positive random variables and peaks over threshold models based on extreme value theory are described in Rootzén and Zholud (2017) <doi:10.1007/s10687-017-0305-5>; Belzile et al. (2021) <doi:10.1098/rsos.202097> and Belzile et al. (2022) <doi:10.1146/annurev-statistics-040120-025426>.

r-larf 1.4
Propagated dependencies: r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=LARF
Licenses: GPL 3
Build system: r
Synopsis: Local Average Response Functions for Instrumental Variable Estimation of Treatment Effects
Description:

This package provides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument are binary. Applicable to both binary and continuous outcomes.

r-ltsk 1.1.2
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=ltsk
Licenses: GPL 2
Build system: r
Synopsis: Local Time Space Kriging
Description:

This package implements local spatial and local spatiotemporal Kriging based on local spatial and local spatiotemporal variograms, respectively. The method is documented in Kumar et al (2013) <https://www.nature.com/articles/jes201352)>.

r-ldavis 0.3.2
Propagated dependencies: r-rjsonio@2.0.0 r-proxy@0.4-27
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/cpsievert/LDAvis
Licenses: Expat
Build system: r
Synopsis: Interactive Visualization of Topic Models
Description:

This package provides tools to create an interactive web-based visualization of a topic model that has been fit to a corpus of text data using Latent Dirichlet Allocation (LDA). Given the estimated parameters of the topic model, it computes various summary statistics as input to an interactive visualization built with D3.js that is accessed via a browser. The goal is to help users interpret the topics in their LDA topic model.

r-lepage 1.0
Propagated dependencies: r-rfast@2.1.5.2
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=LePage
Licenses: GPL 2+
Build system: r
Synopsis: LePage Type Tests
Description:

Location and scale hypothesis testing using the LePage test and variants of its as proposed by Hussain A. and Tsagris M. (2025), <doi:10.48550/arXiv.2509.19126>.

r-lares 5.3.2
Propagated dependencies: r-yaml@2.3.10 r-tidyr@1.3.1 r-stringr@1.6.0 r-rvest@1.0.5 r-rpart-plot@3.1.4 r-rpart@4.1.24 r-rlang@1.1.6 r-proc@1.19.0.1 r-patchwork@1.3.2 r-openxlsx@4.2.8.1 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/laresbernardo/lares
Licenses: AGPL 3
Build system: r
Synopsis: Lean Analytics and Robust Exploration Sidekick
Description:

Auxiliary package for better/faster analytics, visualization, data mining, and machine learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling, Marketing Mix Modeling (Robyn), Exploratory, API, and Scrapper, it helps the analyst or data scientist to get quick and robust results, without the need of repetitive coding or advanced R programming skills.

r-landsepi 1.5.3
Dependencies: gsl@2.8
Propagated dependencies: r-testthat@3.3.0 r-splancs@2.01-45 r-sp@2.2-0 r-sf@1.0-23 r-rsqlite@2.4.4 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-matrix@1.7-4 r-foreach@1.5.2 r-fields@17.1 r-doparallel@1.0.17 r-desolve@1.40 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://landsepi.pages-forge.inrae.fr/landsepi
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Landscape Epidemiology and Evolution
Description:

This package provides a stochastic, spatially-explicit, demo-genetic model simulating the spread and evolution of a plant pathogen in a heterogeneous landscape to assess resistance deployment strategies. It is based on a spatial geometry for describing the landscape and allocation of different cultivars, a dispersal kernel for the dissemination of the pathogen, and a SEIR ('Susceptible-Exposed-Infectious-Removedâ ) structure with a discrete time step. It provides a useful tool to assess the performance of a wide range of deployment options with respect to their epidemiological, evolutionary and economic outcomes. Loup Rimbaud, Julien Papaïx, Jean-François Rey, Luke G Barrett, Peter H Thrall (2018) <doi:10.1371/journal.pcbi.1006067>.

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