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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-mispu 1.0
Propagated dependencies: r-vegan@2.7-2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-cluster@2.1.8.1 r-aspu@1.50 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=MiSPU
Licenses: GPL 2
Build system: r
Synopsis: Microbiome Based Sum of Powered Score (MiSPU) Tests
Description:

There is an increasing interest in investigating how the compositions of microbial communities are associated with human health and disease. In this package, we present a novel global testing method called aMiSPU, that is highly adaptive and thus high powered across various scenarios, alleviating the issue with the choice of a phylogenetic distance. Our simulations and real data analysis demonstrated that aMiSPU test was often more powerful than several competing methods while correctly controlling type I error rates.

r-multiroc 1.1.1
Propagated dependencies: r-zoo@1.8-14 r-magrittr@2.0.4 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=multiROC
Licenses: GPL 3
Build system: r
Synopsis: Calculating and Visualizing ROC and PR Curves Across Multi-Class Classifications
Description:

This package provides tools to solve real-world problems with multiple classes classifications by computing the areas under ROC and PR curve via micro-averaging and macro-averaging. The vignettes of this package can be found via <https://github.com/WandeRum/multiROC>. The methodology is described in V. Van Asch (2013) <https://www.clips.uantwerpen.be/~vincent/pdf/microaverage.pdf> and Pedregosa et al. (2011) <http://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html>.

r-mcount 1.0.0
Propagated dependencies: r-bbmle@1.0.25.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mcount
Licenses: GPL 3
Build system: r
Synopsis: Marginalized Count Regression Models
Description:

Implementation of marginalized models for zero-inflated count data. This package provides a tool to implement an estimation algorithm for the marginalized count models, which directly makes inference on the effect of each covariate on the marginal mean of the outcome. The method involves the marginalized zero-inflated Poisson model described in Long et al. (2014) <doi:10.1002/sim.6293>.

r-mlpwr 1.1.1
Propagated dependencies: r-rlist@0.4.6.2 r-rgenoud@5.9-0.11 r-randtoolbox@2.0.5 r-ggplot2@4.0.1 r-digest@0.6.39 r-dicekriging@1.6.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/flxzimmer/mlpwr
Licenses: GPL 3+
Build system: r
Synopsis: Power Analysis Toolbox to Find Cost-Efficient Study Designs
Description:

We implement a surrogate modeling algorithm to guide simulation-based sample size planning. The method is described in detail in our paper (Zimmer & Debelak (2023) <doi:10.1037/met0000611>). It supports multiple study design parameters and optimization with respect to a cost function. It can find optimal designs that correspond to a desired statistical power or that fulfill a cost constraint. We also provide a tutorial paper (Zimmer et al. (2023) <doi:10.3758/s13428-023-02269-0>).

r-mobsim 0.3.2
Propagated dependencies: r-vegan@2.7-2 r-sads@0.6.5 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/MoBiodiv/mobsim
Licenses: GPL 3+
Build system: r
Synopsis: Spatial Simulation and Scale-Dependent Analysis of Biodiversity Changes
Description:

Simulation, analysis and sampling of spatial biodiversity data (May, Gerstner, McGlinn, Xiao & Chase 2017) <doi:10.1111/2041-210x.12986>. In the simulation tools user define the numbers of species and individuals, the species abundance distribution and species aggregation. Functions for analysis include species rarefaction and accumulation curves, species-area relationships and the distance decay of similarity.

r-mlelod 1.0.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mlelod
Licenses: GPL 2
Build system: r
Synopsis: MLE for Normally Distributed Data Censored by Limit of Detection
Description:

Values below the limit of detection (LOD) are a problem in several fields of science, and there are numerous approaches for replacing the missing data. We present a new mathematical solution for maximum likelihood estimation that allows us to estimate the true values of the mean and standard deviation for normal distributions and is significantly faster than previous implementations. The article with the details was submitted to JSS and can be currently seen on <https://www2.arnes.si/~tverbo/LOD/Verbovsek_Sega_2_Manuscript.pdf>.

r-miebl 0.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=miebl
Licenses: GPL 3
Build system: r
Synopsis: Performance Criteria Modeler for Discrete Trial Training
Description:

This package provides a tool for computing probabilities and other quantities that are relevant in selecting performance criteria for discrete trial training. The main function, miebl(), computes Bayesian and frequentist probabilities and bounds for each of n possible performance criterion choices when attempting to determine a student's true mastery level by counting their number of successful attempts at displaying learning among n trials. The reporting function miebl_re() takes output from miebl() and prepares it into a brief report for a specific criterion. miebl_cp() combines 2 to 5 distributions of true mastery level given performance criterion in one plot for comparison. Ramos (2025) <doi:10.1007/s40617-025-01058-9>.

r-mnlfa 0.3-4
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-cdm@8.3-14
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/alexanderrobitzsch/mnlfa
Licenses: GPL 2+
Build system: r
Synopsis: Moderated Nonlinear Factor Analysis
Description:

Conducts moderated nonlinear factor analysis (e.g., Curran et al., 2014, <doi:10.1080/00273171.2014.889594>). Regularization methods are implemented for assessing non-invariant items. Currently, the package includes dichotomous items and unidimensional item response models. Extensions will be included in future package versions.

r-mrcv 0.4-0
Propagated dependencies: r-tables@0.9.33
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MRCV
Licenses: GPL 3+
Build system: r
Synopsis: Methods for Analyzing Multiple Response Categorical Variables (MRCVs)
Description:

This package provides functions for analyzing the association between one single response categorical variable (SRCV) and one multiple response categorical variable (MRCV), or between two or three MRCVs. A modified Pearson chi-square statistic can be used to test for marginal independence for the one or two MRCV case, or a more general loglinear modeling approach can be used to examine various other structures of association for the two or three MRCV case. Bootstrap- and asymptotic-based standardized residuals and model-predicted odds ratios are available, in addition to other descriptive information. Statisical methods implemented are described in Bilder et al. (2000) <doi:10.1080/03610910008813665>, Bilder and Loughin (2004) <doi:10.1111/j.0006-341X.2004.00147.x>, Bilder and Loughin (2007) <doi:10.1080/03610920600974419>, and Koziol and Bilder (2014) <https://journal.r-project.org/articles/RJ-2014-014/>.

r-messi 0.1.2
Propagated dependencies: r-progress@1.2.3 r-patchwork@1.3.2 r-mass@7.3-65 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/umich-cphds/messi
Licenses: GPL 2
Build system: r
Synopsis: Mediation with External Summary Statistic Information
Description:

Fits the MESSI, hard constraint, and unconstrained models in Boss et al. (2023) <doi:10.48550/arXiv.2306.17347> for mediation analyses with external summary-level information on the total effect.

r-midoc 1.0.0
Propagated dependencies: r-rmarkdown@2.30 r-rlang@1.1.6 r-mice@3.18.0 r-mfp2@1.0.1 r-lifecycle@1.0.4 r-glue@1.8.0 r-dagitty@0.3-4 r-blorr@0.3.1 r-arm@1.14-4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://elliecurnow.github.io/midoc/
Licenses: Expat
Build system: r
Synopsis: Decision-Making System for Multiple Imputation
Description:

This package provides a guidance system for analysis with missing data. It incorporates expert, up-to-date methodology to help researchers choose the most appropriate analysis approach when some data are missing. You provide the available data and the assumed causal structure, including the likely causes of missing data. midoc will advise which analysis approaches can be used, and how best to perform them. midoc follows the framework for the treatment and reporting of missing data in observational studies (TARMOS). Lee et al (2021). <doi:10.1016/j.jclinepi.2021.01.008>.

r-monte-carlo-se 0.1.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=Monte.Carlo.se
Licenses: GPL 3
Build system: r
Synopsis: Monte Carlo Standard Errors
Description:

Computes Monte Carlo standard errors for summaries of Monte Carlo output. Summaries and their standard errors are based on columns of Monte Carlo simulation output. Dennis D. Boos and Jason A. Osborne (2015) <doi:10.1111/insr.12087>.

r-mlr3oml 0.12.0
Propagated dependencies: r-withr@3.0.2 r-uuid@1.2-1 r-stringi@1.8.7 r-r6@2.6.1 r-paradox@1.0.1 r-mlr3misc@0.19.0 r-mlr3@1.2.0 r-lgr@0.5.0 r-jsonlite@2.0.0 r-data-table@1.17.8 r-curl@7.0.0 r-checkmate@2.3.3 r-bit64@4.6.0-1 r-backports@1.5.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://mlr3oml.mlr-org.com
Licenses: LGPL 3
Build system: r
Synopsis: Connector Between 'mlr3' and 'OpenML'
Description:

This package provides an interface to OpenML.org to list and download machine learning data, tasks and experiments. The OpenML objects can be automatically converted to mlr3 objects. For a more sophisticated interface with more upload options, see the OpenML package.

r-mvalpha 0.5.1
Propagated dependencies: r-rlang@1.1.6 r-rdpack@2.6.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/therealcfdrake/mvalpha
Licenses: AGPL 3+
Build system: r
Synopsis: Krippendorff's Alpha for Multi-Valued Data
Description:

Calculate Krippendorff's alpha for multi-valued data using the methods introduced by Krippendorff and Craggs (2016) <doi:10.1080/19312458.2016.1228863>. Nominal, ordinal, interval, and ratio data types are supported, with options to create bootstrapped estimates of alpha and/or parallelize calculations.

r-mreg 1.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/shug0131/mreg
Licenses: GPL 3+
Build system: r
Synopsis: Fits Regression Models When the Outcome is Partially Missing
Description:

This package implements the methods described in Bond S, Farewell V, 2006, Exact Likelihood Estimation for a Negative Binomial Regression Model with Missing Outcomes, Biometrics.

r-mondrian 1.1.2
Propagated dependencies: r-rcolorbrewer@1.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=Mondrian
Licenses: GPL 2+
Build system: r
Synopsis: Simple Graphical Representation of the Relative Occurrence and Co-Occurrence of Events
Description:

The unique function of this package allows representing in a single graph the relative occurrence and co-occurrence of events measured in a sample. As examples, the package was applied to describe the occurrence and co-occurrence of different species of bacterial or viral symbionts infecting arthropods at the individual level. The graphics allows determining the prevalence of each symbiont and the patterns of multiple infections (i.e. how different symbionts share or not the same individual hosts). We named the package after the famous painter as the graphical output recalls Mondrianâ s paintings.

r-mtest 1.0.4
Propagated dependencies: r-plotly@4.11.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/vmoprojs/MTest
Licenses: GPL 3+
Build system: r
Synopsis: Procedure for Multicollinearity Testing using Bootstrap
Description:

This package provides functions for detecting multicollinearity. This test gives statistical support to two of the most famous methods for detecting multicollinearity in applied work: Kleinâ s rule and Variance Inflation Factor (VIF). See the URL for the papers associated with this package, as for instance, Morales-Oñate and Morales-Oñate (2015) <doi:10.33333/rp.vol51n2.05>.

r-mcid 0.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MCID
Licenses: GPL 2+
Build system: r
Synopsis: Estimating the Minimal Clinically Important Difference
Description:

Apply the marginal classification method to achieve the purpose of providing the point and interval estimates for the minimal clinically important difference based on the classical anchor-based method. For more details of the methodology, please see Zehua Zhou, Leslie J. Bisson and Jiwei Zhao (2021) <arXiv:2108.11589>.

r-magma-r 1.0.4
Propagated dependencies: r-tidyverse@2.0.0 r-tidyselect@1.2.1 r-tibble@3.3.0 r-stddiff@3.1 r-robumeta@2.1 r-rlang@1.1.6 r-purrr@1.2.0 r-psych@2.5.6 r-overlapping@2.4 r-metafor@4.8-0 r-janitor@2.2.1 r-ggplot2@4.0.1 r-foreach@1.5.2 r-flextable@0.9.10 r-dplyr@1.1.4 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MAGMA.R
Licenses: GPL 3
Build system: r
Synopsis: MAny-Group MAtching
Description:

Balancing quasi-experimental field research for effects of covariates is fundamental for drawing causal inference. Propensity Score Matching deals with this issue but current techniques are restricted to binary treatment variables. Moreover, they provide several solutions without providing a comprehensive framework on choosing the best model. The MAGMA R-package addresses these restrictions by offering nearest neighbor matching for two to four groups. It also includes the option to match data of a 2x2 design. In addition, MAGMA includes a framework for evaluating the post-matching balance. The package includes functions for the matching process and matching reporting. We provide a tutorial on MAGMA as vignette. More information on MAGMA can be found in Feuchter, M. D., Urban, J., Scherrer V., Breit, M. L., and Preckel F. (2022) <https://osf.io/p47nc/>.

r-mycor 0.1.1
Propagated dependencies: r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/cardiomoon/mycor
Licenses: CC0
Build system: r
Synopsis: Automatic Correlation and Regression Test in a 'data.frame'
Description:

Perform correlation and linear regression test among the numeric fields in a data.frame automatically and make plots using pairs or lattice::parallelplot.

r-mupet 0.1.0
Propagated dependencies: r-yardstick@1.3.2 r-rlang@1.1.6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/astamm/mupet
Licenses: Expat
Build system: r
Synopsis: Multiclass Performance Evaluation Toolkit
Description:

Implementation of custom tidymodels metrics for multi-class prediction models with a single negative class. Currently are implemented macro-average sensitivity and specificity as in Mortaz, Ebrahim (2020) "Imbalance accuracy metric for model selection in multi-class imbalance classification problemsâ <doi:10.1016/j.knosys.2020.106490> and a generalized weighted Youden index as in Li, D.L., Shen F., Yin Y., Peng J.X and Chen P.Y. (2013) â Weighted Youden index and its two-independent-sample comparison based on weighted sensitivity and specificityâ <doi:10.3760/cma.j.issn.0366-6999.20123102>.

r-mpspline2 0.1.9
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/obrl-soil/mpspline2
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Mass-Preserving Spline Functions for Soil Data
Description:

This package provides a low-dependency implementation of GSIF::mpspline() <https://r-forge.r-project.org/scm/viewvc.php/pkg/R/mpspline.R?view=markup&revision=240&root=gsif>, which applies a mass-preserving spline to soil attributes. Splining soil data is a safe way to make continuous down-profile estimates of attributes measured over discrete, often discontinuous depth intervals.

r-mvtmeta 1.1
Propagated dependencies: r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mvtmeta
Licenses: GPL 3
Build system: r
Synopsis: Multivariate Meta-Analysis
Description:

This package provides functions to run fixed effects or random effects multivariate meta-analysis.

r-multilink 0.1.1
Propagated dependencies: r-stringr@1.6.0 r-recordlinkage@0.4-12.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mcclust@1.0.1 r-igraph@2.2.1 r-geosphere@1.5-20
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/aleshing/multilink
Licenses: GPL 3
Build system: r
Synopsis: Multifile Record Linkage and Duplicate Detection
Description:

Implementation of the methodology of Aleshin-Guendel & Sadinle (2022) <doi:10.1080/01621459.2021.2013242>. It handles the general problem of multifile record linkage and duplicate detection, where any number of files are to be linked, and any of the files may have duplicates.

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