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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-memify 0.1.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=memify
Licenses: GPL 3
Build system: r
Synopsis: Constructing Functions That Keep State
Description:

This package provides a simple way to construct and maintain functions that keep state i.e. remember their argument lists. This can be useful when one needs to repeatedly invoke the same function with only a small number of argument changes at each invocation.

r-madtests 0.1.1
Propagated dependencies: r-gld@2.6.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MADtests
Licenses: Expat
Build system: r
Synopsis: Hypothesis Tests and Confidence Intervals for Median Absolute Deviations
Description:

Conducts one- and two-sample hypothesis tests for median absolute deviations (mads) for robust inference of dispersion. Comparisons between two samples uses the ratio of mads. Confidence intervals are also computed.

r-mpwr 0.1.5.1
Propagated dependencies: r-upsetr@1.4.0 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-purrr@1.2.0 r-plotly@4.11.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-forcats@1.0.1 r-flowtracer@0.1.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-comprehenr@0.6.10
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mpwR
Licenses: Expat
Build system: r
Synopsis: Standardized Comparison of Workflows in Mass Spectrometry-Based Bottom-Up Proteomics
Description:

Useful functions to analyze proteomic workflows including number of identifications, data completeness, missed cleavages, quantitative and retention time precision etc. Various software outputs are supported such as ProteomeDiscoverer', Spectronaut', DIA-NN and MaxQuant'.

r-mize 0.2.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/jlmelville/mize
Licenses: FSDG-compatible
Build system: r
Synopsis: Unconstrained Numerical Optimization Algorithms
Description:

Optimization algorithms implemented in R, including conjugate gradient (CG), Broyden-Fletcher-Goldfarb-Shanno (BFGS) and the limited memory BFGS (L-BFGS) methods. Most internal parameters can be set through the call interface. The solvers hold up quite well for higher-dimensional problems.

r-mpsem 0.6-1
Propagated dependencies: r-mass@7.3-65 r-magrittr@2.0.4 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MPSEM
Licenses: GPL 3
Build system: r
Synopsis: Modelling Phylogenetic Signals using Eigenvector Maps
Description:

Computational tools to represent phylogenetic signals using adapted eigenvector maps.

r-meboot 1.5
Propagated dependencies: r-nlme@3.1-168 r-hdrcde@3.4 r-dynlm@0.3-6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=meboot
Licenses: GPL 2+
Build system: r
Synopsis: Maximum Entropy Bootstrap for Time Series
Description:

Maximum entropy density based dependent data bootstrap. An algorithm is provided to create a population of time series (ensemble) without assuming stationarity. The reference paper (Vinod, H.D., 2004 <DOI:10.1016/j.jempfin.2003.06.002>) explains how the algorithm satisfies the ergodic theorem and the central limit theorem.

r-mtsta 0.0.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/PaulESantos/mtsta
Licenses: Expat
Build system: r
Synopsis: Accessing the Red List of Montane Tree Species of the Tropical Andes
Description:

Access the Red List of Montane Tree Species of the Tropical Andes Tejedor Garavito et al.(2014, ISBN:978-1-905164-60-8). This package allows users to search for globally threatened tree species within the andean montane forests, including cloud forests and seasonal (wet) forests above 1500 m a.s.l.

r-minedfind 0.1.3
Propagated dependencies: r-iso@0.0-21 r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MinEDfind
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Design for Minimum Effective Dosing-Finding Trial
Description:

The nonparametric two-stage Bayesian adaptive design is a novel phase II clinical trial design for finding the minimum effective dose (MinED). This design is motivated by the top priority and concern of clinicians when testing a new drug, which is to effectively treat patients and minimize the chance of exposing them to subtherapeutic or overly toxic doses. It is used to design single-agent trials.

r-microdatoses 0.8.15
Propagated dependencies: r-readr@2.1.6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://www.datanalytics.com/2012/08/06/un-paseo-por-el-paquete-microdatoses-y-la-epa-de-nuevo/
Licenses: GPL 3
Build system: r
Synopsis: Utilities for Official Spanish Microdata
Description:

This package provides utilities for reading and processing microdata from Spanish official statistics with R.

r-mtvc 1.1.0
Propagated dependencies: r-tidyr@1.3.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/egonzato/mtvc
Licenses: Expat
Build system: r
Synopsis: Multiple Counting Process Structure for Survival Analysis
Description:

Counting process structure is fundamental to model time varying covariates. This package restructures dataframes in the counting process format for one or more variables. F. W. Dekker, et al. (2008) <doi:10.1038/ki.2008.328>.

r-methcomp 1.30.2
Dependencies: jags@4.3.1
Propagated dependencies: r-nlme@3.1-168 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://BendixCarstensen.com/MethComp/
Licenses: GPL 2+
Build system: r
Synopsis: Analysis of Agreement in Method Comparison Studies
Description:

This package provides methods (standard and advanced) for analysis of agreement between measurement methods. These cover Bland-Altman plots, Deming regression, Lin's Total deviation index, and difference-on-average regression. See Carstensen B. (2010) "Comparing Clinical Measurement Methods: A Practical Guide (Statistics in Practice)" <doi:10.1002/9780470683019> for more information.

r-moc-gapbk 0.1.3
Propagated dependencies: r-nsga2r@1.1 r-foreach@1.5.2 r-dosnow@1.0.20 r-doparallel@1.0.17 r-dompi@0.2.2 r-amap@0.8-20
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=moc.gapbk
Licenses: GPL 2
Build system: r
Synopsis: Multi-Objective Clustering Algorithm Guided by a-Priori Biological Knowledge
Description:

This package implements the Multi-Objective Clustering Algorithm Guided by a-Priori Biological Knowledge (MOC-GaPBK) which was proposed by Parraga-Alava, J. et. al. (2018) <doi:10.1186/s13040-018-0178-4>.

r-mldatar 1.0.1
Propagated dependencies: r-workflows@1.3.0 r-varhandle@2.0.6 r-rsample@1.3.1 r-recipes@1.3.1 r-ranger@0.17.0 r-parsnip@1.3.3 r-oddsplotty@1.0.2 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-confusiontabler@1.0.4 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MLDataR
Licenses: Expat
Build system: r
Synopsis: Collection of Machine Learning Datasets for Supervised Machine Learning
Description:

This package contains a collection of datasets for working with machine learning tasks. It will contain datasets for supervised machine learning Jiang (2020)<doi:10.1016/j.beth.2020.05.002> and will include datasets for classification and regression. The aim of this package is to use data generated around health and other domains.

r-mus 0.1.6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MUS
Licenses: GPL 2+
Build system: r
Synopsis: Monetary Unit Sampling and Estimation Methods, Widely Used in Auditing
Description:

Sampling and evaluation methods to apply Monetary Unit Sampling (or in older literature Dollar Unit Sampling) during an audit of financial statements.

r-modelbpp 0.1.6
Propagated dependencies: r-pbapply@1.7-4 r-manymome@0.3.3 r-lavaan@0.6-20 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://sfcheung.github.io/modelbpp/
Licenses: GPL 3+
Build system: r
Synopsis: Model BIC Posterior Probability
Description:

Fits the neighboring models of a fitted structural equation model and assesses the model uncertainty of the fitted model based on BIC posterior probabilities, using the method presented in Wu, Cheung, and Leung (2020) <doi:10.1080/00273171.2019.1574546>.

r-maplegend 0.5.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/riatelab/maplegend/
Licenses: GPL 3
Build system: r
Synopsis: Legends for Maps
Description:

Create legends for maps and other graphics. Thematic maps need to be accompanied by legible legends to be fully comprehensible. This package offers a wide range of legends useful for cartography, some of which may also be useful for other types of graphics.

r-multordrs 0.1-3
Propagated dependencies: r-statmod@1.5.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MultOrdRS
Licenses: GPL 2+
Build system: r
Synopsis: Model Multivariate Ordinal Responses Including Response Styles
Description:

In the case of multivariate ordinal responses, parameter estimates can be severely biased if personal response styles are ignored. This packages provides methods to account for personal response styles and to explain the effects of covariates on the response style, as proposed by Schauberger and Tutz 2021 <doi:10.1177/1471082X20978034>. The method is implemented both for the multivariate cumulative model and the multivariate adjacent categories model.

r-mkpower 1.1
Propagated dependencies: r-rlang@1.1.6 r-qqplotr@0.0.7 r-mvtnorm@1.3-3 r-mkinfer@1.3 r-mkdescr@0.9 r-matrixtests@0.2.3.1 r-ggplot2@4.0.1 r-coin@1.4-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/stamats/MKpower
Licenses: LGPL 3
Build system: r
Synopsis: Power Analysis and Sample Size Calculation
Description:

Power analysis and sample size calculation for Welch and Hsu (Hedderich and Sachs (2018), ISBN:978-3-662-56657-2) t-tests including Monte-Carlo simulations of empirical power and type-I-error. Power and sample size calculation for Wilcoxon rank sum and signed rank tests via Monte-Carlo simulations. Power and sample size required for the evaluation of a diagnostic test(-system) (Flahault et al. (2005), <doi:10.1016/j.jclinepi.2004.12.009>; Dobbin and Simon (2007), <doi:10.1093/biostatistics/kxj036>) as well as for a single proportion (Fleiss et al. (2003), ISBN:978-0-471-52629-2; Piegorsch (2004), <doi:10.1016/j.csda.2003.10.002>; Thulin (2014), <doi:10.1214/14-ejs909>), comparing two negative binomial rates (Zhu and Lakkis (2014), <doi:10.1002/sim.5947>), ANCOVA (Shieh (2020), <doi:10.1007/s11336-019-09692-3>), reference ranges (Jennen-Steinmetz and Wellek (2005), <doi:10.1002/sim.2177>), multiple primary endpoints (Sozu et al. (2015), ISBN:978-3-319-22005-5), and AUC (Hanley and McNeil (1982), <doi:10.1148/radiology.143.1.7063747>).

r-mlts 2.0.1
Propagated dependencies: r-stanheaders@2.32.10 r-shape@1.4.6.1 r-rstantools@2.5.0 r-rstan@2.32.7 r-rmarkdown@2.30 r-rlang@1.1.6 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-pdftools@3.6.0 r-mvtnorm@1.3-3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-diagram@1.6.5 r-cowplot@1.2.0 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/munchfab/mlts
Licenses: GPL 3+
Build system: r
Synopsis: Multilevel Latent Time Series Models with 'R' and 'Stan'
Description:

Fit multilevel manifest or latent time-series models, including popular Dynamic Structural Equation Models (DSEM). The models can be set up and modified with user-friendly functions and are fit to the data using Stan for Bayesian inference. Path models and formulas for user-defined models can be easily created with functions using knitr'. Asparouhov, Hamaker, & Muthen (2018) <doi:10.1080/10705511.2017.1406803>.

r-mrtsamplesizebinary 0.1.2
Propagated dependencies: r-matrix@1.7-4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MRTSampleSizeBinary
Licenses: GPL 3
Build system: r
Synopsis: Sample Size Calculator for MRT with Binary Outcomes
Description:

This package provides a sample size calculator for micro-randomized trials (MRTs) with binary outcomes based on Cohn et al. (2023) <doi:10.1002/sim.9748>. Also provides a power calculator when the sample size is input by the user.

r-mmaqshiny 1.0.0
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-xml@3.99-0.20 r-stringr@1.6.0 r-shinyjs@2.1.0 r-shiny@1.11.1 r-plotly@4.11.0 r-lubridate@1.9.4 r-leaflet@2.2.3 r-htmltools@0.5.8.1 r-ggplot2@4.0.1 r-dt@0.34.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-catools@1.18.3 r-cairo@1.7-0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/meenakshi-kushwaha/mmaqshiny
Licenses: Expat
Build system: r
Synopsis: Explore Air-Quality Mobile-Monitoring Data
Description:

Mobile-monitoring or "sensors on a mobile platform", is an increasingly popular approach to measure high-resolution pollution data at the street level. Coupled with location data, spatial visualisation of air-quality parameters helps detect localized areas of high air-pollution, also called hotspots. In this approach, portable sensors are mounted on a vehicle and driven on predetermined routes to collect high frequency data (1 Hz). mmaqshiny is for analysing, visualising and spatial mapping of high-resolution air-quality data collected by specific devices installed on a moving platform. 1 Hz data of PM2.5 (mass concentrations of particulate matter with size less than 2.5 microns), Black carbon mass concentrations (BC), ultra-fine particle number concentrations, carbon dioxide along with GPS coordinates and relative humidity (RH) data collected by popular portable instruments (TSI DustTrak-8530, Aethlabs microAeth-AE51, TSI CPC3007, LICOR Li-830, Garmin GPSMAP 64s, Omega USB RH probe respectively). It incorporates device specific cleaning and correction algorithms. RH correction is applied to DustTrak PM2.5 following the Chakrabarti et al., (2004) <doi:10.1016/j.atmosenv.2004.03.007>. Provision is given to add linear regression coefficients for correcting the PM2.5 data (if required). BC data will be cleaned for the vibration generated noise, by adopting the statistical procedure as explained in Apte et al., (2011) <doi:10.1016/j.atmosenv.2011.05.028>, followed by a loading correction as suggested by Ban-Weiss et al., (2009) <doi:10.1021/es8021039>. For the number concentration data, provision is given for dilution correction factor (if a diluter is used with CPC3007; default value is 1). The package joins the raw, cleaned and corrected data from the above said instruments and outputs as a downloadable csv file.

r-mc-heterogeneity 0.1.2
Propagated dependencies: r-metafor@4.8-0 r-boot-heterogeneity@1.1.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mc.heterogeneity
Licenses: GPL 2+
Build system: r
Synopsis: Monte Carlo Based Heterogeneity Test for Meta-Analysis
Description:

This package implements a Monte Carlo Based Heterogeneity Test for standardized mean differences (d), Fisher-transformed Pearson's correlations (r), and natural-logarithm-transformed odds ratio (OR) in Meta-Analysis Studies. Depending on the presence of moderators, this Monte Carlo Based Test can be implemented in the random or mixed-effects model. This package uses rma() function from the R package metafor to obtain parameter estimates and likelihood, so installation of R package metafor is required. This approach refers to the studies of Hedges (1981) <doi:10.3102/10769986006002107>, Hedges & Olkin (1985, ISBN:978-0123363800), Silagy, Lancaster, Stead, Mant, & Fowler (2004) <doi:10.1002/14651858.CD000146.pub2>, Viechtbauer (2010) <doi:10.18637/jss.v036.i03>, and Zuckerman (1994, ISBN:978-0521432009).

r-msclassifr 0.5.0
Propagated dependencies: r-statmod@1.5.1 r-reshape2@1.4.5 r-rcpp@1.1.0 r-matrix@1.7-4 r-maldirppa@1.1.0-3 r-maldiquant@1.22.3 r-limma@3.66.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-cp4p@0.3.6 r-caret@7.0-1 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/agodmer/MSclassifR_examples
Licenses: GPL 3+
Build system: r
Synopsis: Automated Classification of Mass Spectra
Description:

This package provides functions to classify mass spectra in known categories and to determine discriminant mass-to-charge values (m/z). Includes easy-to-use preprocessing pipelines for Matrix Assisted Laser Desorption Ionisation - Time Of Flight Mass Spectrometry (MALDI-TOF) mass spectra, methods to select discriminant m/z from labelled libraries, and tools to predict categories (species, phenotypes, etc.) from selected features. Also provides utilities to build design matrices from peak intensities and labels. While this package was developed with the aim of identifying very similar species or phenotypes of bacteria from MALDI-TOF MS, the functions of this package can also be used to classify other categories associated to mass spectra; or from mass spectra obtained with other mass spectrometry techniques. Parallelized processing and optional C++-accelerated functions are available (notably to deal with large datasets) from version 0.5.0. If you use this package in your research, please cite the associated publication (<doi:10.1016/j.eswa.2025.128796>). For a comprehensive guide, additional applications, and detailed examples, see <https://github.com/agodmer/MSclassifR_examples>.

r-mdccure 0.1.0
Dependencies: tbb@2021.6.0
Propagated dependencies: r-survival@3.8-3 r-smcure@2.2 r-rcppparallel@5.1.11-1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-npcure@0.1-5 r-gridextra@2.3 r-ggtext@0.1.2 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-future@1.68.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/CastleMon/MDCcure
Licenses: GPL 3
Build system: r
Synopsis: Martingale Dependence Tools and Testing for Mixture Cure Models
Description:

Computes martingale difference correlation (MDC), martingale difference divergence, and their partial extensions to assess conditional mean dependence. The methods are based on Shao and Zhang (2014) <doi:10.1080/01621459.2014.887012>. Additionally, introduces a novel hypothesis test for evaluating covariate effects on the cure rate in mixture cure models, using MDC-based statistics. The methodology is described in Monroy-Castillo et al. (2025, manuscript submitted).

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Total results: 68655