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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-pomcheckr 0.1.1
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pomcheckr
Licenses: Expat
Build system: r
Synopsis: Graphical Check for Proportional Odds Assumption
Description:

This package implements the method described at the UCLA Statistical Consulting site <https://stats.idre.ucla.edu/r/dae/ordinal-logistic-regression/> for checking if the proportional odds assumption holds for a cumulative logit model.

r-plotmm 0.1.2
Propagated dependencies: r-wesanderson@0.3.7 r-mixtools@2.0.0.1 r-ggplot2@4.0.1 r-flexmix@2.3-20 r-emcluster@0.2-17 r-amerika@0.1.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=plotmm
Licenses: Expat
Build system: r
Synopsis: Tidy Tools for Visualizing Mixture Models
Description:

The main function, plot_mm(), is used for (gg)plotting output from mixture models, including both densities and overlaying mixture weight component curves from the fit models in line with the tidy principles. The package includes several additional functions for added plot customization. Supported model objects include: mixtools', EMCluster', and flexmix', with more from each in active dev. Supported mixture model specifications include mixtures of univariate Gaussians, multivariate Gaussians, Gammas, logistic regressions, linear regressions, and Poisson regressions.

r-pathviewr 1.1.8
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-r-matlab@3.7.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-fancova@0.6-1 r-dplyr@1.1.4 r-data-table@1.17.8 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/ropensci/pathviewr/
Licenses: GPL 3
Build system: r
Synopsis: Wrangle, Analyze, and Visualize Animal Movement Data
Description:

This package provides tools to import, clean, and visualize movement data, particularly from motion capture systems such as Optitrack's Motive', the Straw Lab's Flydra', or from other sources. We provide functions to remove artifacts, standardize tunnel position and tunnel axes, select a region of interest, isolate specific trajectories, fill gaps in trajectory data, and calculate 3D and per-axis velocity. For experiments of visual guidance, we also provide functions that use subject position to estimate perception of visual stimuli.

r-phdcocktail 0.1.0
Propagated dependencies: r-scales@1.4.0 r-rstudioapi@0.17.1 r-rcolorbrewer@1.1-3 r-here@1.0.2 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://dahhamalsoud.github.io/phdcocktail/
Licenses: Expat
Build system: r
Synopsis: Enhance the Ease of R Experience as an Emerging Researcher
Description:

This package provides a toolkit of functions to help: i) effortlessly transform collected data into a publication ready format, ii) generate insightful visualizations from clinical data, iii) report summary statistics in a publication-ready format, iv) efficiently export, save and reload R objects within the framework of R projects.

r-pac 1.1.6
Propagated dependencies: r-rtsne@0.17 r-rcpp@1.1.0 r-parmigene@1.1.1 r-infotheo@1.2.0.1 r-igraph@2.2.1 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://doi.org/10.1371/journal.pcbi.1005875
Licenses: GPL 3
Build system: r
Synopsis: Partition-Assisted Clustering and Multiple Alignments of Networks
Description:

This package implements partition-assisted clustering and multiple alignments of networks. It 1) utilizes partition-assisted clustering to find robust and accurate clusters and 2) discovers coherent relationships of clusters across multiple samples. It is particularly useful for analyzing single-cell data set. Please see Li et al. (2017) <doi:10.1371/journal.pcbi.1005875> for detail method description.

r-paleots 0.6.2
Propagated dependencies: r-mnormt@2.1.1 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=paleoTS
Licenses: GPL 3
Build system: r
Synopsis: Analyze Paleontological Time-Series
Description:

Facilitates analysis of paleontological sequences of trait values. Functions are provided to fit, using maximum likelihood, simple evolutionary models (including unbiased random walks, directional evolution,stasis, Ornstein-Uhlenbeck, covariate-tracking) and complex models (punctuation, mode shifts).

r-presenceabsence 1.1.11
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PresenceAbsence
Licenses: FSDG-compatible
Build system: r
Synopsis: Presence-Absence Model Evaluation
Description:

This package provides a set of functions useful when evaluating the results of presence-absence models. Package includes functions for calculating threshold dependent measures such as confusion matrices, pcc, sensitivity, specificity, and Kappa, and produces plots of each measure as the threshold is varied. It will calculate optimal threshold choice according to a choice of optimization criteria. It also includes functions to plot the threshold independent ROC curves along with the associated AUC (area under the curve).

r-polyrad 2.0.0
Propagated dependencies: r-stringi@1.8.7 r-rcpp@1.1.0 r-pcamethods@2.2.0 r-fastmatch@1.1-6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/lvclark/polyRAD
Licenses: GPL 2+
Build system: r
Synopsis: Genotype Calling with Uncertainty from Sequencing Data in Polyploids and Diploids
Description:

Read depth data from genotyping-by-sequencing (GBS) or restriction site-associated DNA sequencing (RAD-seq) are imported and used to make Bayesian probability estimates of genotypes in polyploids or diploids. The genotype probabilities, posterior mean genotypes, or most probable genotypes can then be exported for downstream analysis. polyRAD is described by Clark et al. (2019) <doi:10.1534/g3.118.200913>, and the Hind/He statistic for marker filtering is described by Clark et al. (2022) <doi:10.1186/s12859-022-04635-9>. A variant calling pipeline for highly duplicated genomes is also included and is described by Clark et al. (2020, Version 1) <doi:10.1101/2020.01.11.902890>.

r-pastboon 0.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pastboon
Licenses: Artistic License 2.0
Build system: r
Synopsis: Simulation of Parameterized Stochastic Boolean Networks
Description:

This package provides a Boolean network is a particular kind of discrete dynamical system where the variables are simple binary switches. Despite its simplicity, Boolean network modeling has been a successful method to describe the behavioral pattern of various phenomena. Applying stochastic noise to Boolean networks is a useful approach for representing the effects of various perturbing stimuli on complex systems. A number of methods have been developed to control noise effects on Boolean networks using parameters integrated into the update rules. This package provides functions to examine three such methods: Boolean network with perturbations (BNp), described by Trairatphisan et al. (2013) <doi:10.1186/1478-811X-11-46>, stochastic discrete dynamical systems (SDDS), proposed by Murrugarra et al. (2012) <doi:10.1186/1687-4153-2012-5>, and Boolean network with probabilistic edge weights (PEW), presented by Deritei et al. (2022) <doi:10.1371/journal.pcbi.1010536>. This package includes source code derived from the BoolNet package, which is licensed under the Artistic License 2.0.

r-player 0.1.0
Propagated dependencies: r-withr@3.0.2 r-twenty48@0.2.1 r-stringr@1.6.0 r-rlang@1.1.6 r-r6@2.6.1 r-purrr@1.2.0 r-plu@0.3.0 r-nnet@7.3-20 r-glue@1.8.0 r-dplyr@1.1.4 r-crayon@1.5.3 r-cli@3.6.5 r-and@0.1.7
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/rossellhayes/player
Licenses: Expat
Build system: r
Synopsis: Play Games in the Console
Description:

Games that can be played in the R console. Includes coin flip, hangman, jumble, magic 8 ball, poker, rock paper scissors, shut the box, spelling bee, and 2048.

r-phenotyper 0.3.2
Propagated dependencies: r-vctrs@0.6.5 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-patientprofiles@1.4.5 r-omopsketch@1.0.1 r-omopgenerics@1.3.6 r-measurementdiagnostics@0.2.0 r-incidenceprevalence@1.2.1 r-drugutilisation@1.1.0 r-dplyr@1.1.4 r-cohortconstructor@0.6.1 r-cohortcharacteristics@1.1.1 r-codelistgenerator@4.0.2 r-clock@0.7.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://ohdsi.github.io/PhenotypeR/
Licenses: FSDG-compatible
Build system: r
Synopsis: Assess Study Cohorts Using a Common Data Model
Description:

Phenotype study cohorts in data mapped to the Observational Medical Outcomes Partnership Common Data Model. Diagnostics are run at the database, code list, cohort, and population level to assess whether study cohorts are ready for research.

r-polyreg 0.8.0
Propagated dependencies: r-nnet@7.3-20
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/matloff/polyreg
Licenses: GPL 2+
Build system: r
Synopsis: Polynomial Regression
Description:

Automate formation and evaluation of polynomial regression models. The motivation for this package is described in Polynomial Regression As an Alternative to Neural Nets by Xi Cheng, Bohdan Khomtchouk, Norman Matloff, and Pete Mohanty (<arXiv:1806.06850>).

r-pixiedust 0.9.4
Propagated dependencies: r-scales@1.4.0 r-reshape2@1.4.5 r-magrittr@2.0.4 r-labelvector@0.1.2 r-knitr@1.50 r-htmltools@0.5.8.1 r-checkmate@2.3.3 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/nutterb/pixiedust
Licenses: GPL 2+
Build system: r
Synopsis: Tables so Beautifully Fine-Tuned You Will Believe It's Magic
Description:

The introduction of the broom package has made converting model objects into data frames as simple as a single function. While the broom package focuses on providing tidy data frames that can be used in advanced analysis, it deliberately stops short of providing functionality for reporting models in publication-ready tables. pixiedust provides this functionality with a programming interface intended to be similar to ggplot2's system of layers with fine tuned control over each cell of the table. Options for output include printing to the console and to the common markdown formats (markdown, HTML, and LaTeX). With a little pixiedust (and happy thoughts) tables can really fly.

r-precmed 1.1.0
Propagated dependencies: r-tidyr@1.3.1 r-survival@3.8-3 r-stringr@1.6.0 r-rlang@1.1.6 r-randomforestsrc@2.9.3 r-mgcv@1.9-4 r-mass@7.3-65 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-gbm@2.2.2 r-gam@1.22-6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/smartdata-analysis-and-statistics/precmed
Licenses: ASL 2.0
Build system: r
Synopsis: Precision Medicine
Description:

This package provides a doubly robust precision medicine approach to fit, cross-validate and visualize prediction models for the conditional average treatment effect (CATE). It implements doubly robust estimation and semiparametric modeling approach of treatment-covariate interactions as proposed by Yadlowsky et al. (2020) <doi:10.1080/01621459.2020.1772080>.

r-pseval 1.3.3
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://sachsmc.github.io/pseval/
Licenses: Expat
Build system: r
Synopsis: Methods for Evaluating Principal Surrogates of Treatment Response
Description:

This package contains the core methods for the evaluation of principal surrogates in a single clinical trial. Provides a flexible interface for defining models for the risk given treatment and the surrogate, the models for integration over the missing counterfactual surrogate responses, and the estimation methods. Estimated maximum likelihood and pseudo-score can be used for estimation, and the bootstrap for inference. A variety of post-estimation summary methods are provided, including print, summary, plot, and testing.

r-pullword 0.3
Propagated dependencies: r-rcurl@1.98-1.17
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pullword
Licenses: LGPL 2.0+
Build system: r
Synopsis: R Interface to Pullword Service
Description:

R Interface to Pullword Service for natural language processing in Chinese. It enables users to extract valuable words from text by deep learning models. For more details please visit the official site (in Chinese) <http://www.pullword.com/>.

r-patterns 1.7
Propagated dependencies: r-wgcna@1.73 r-vgam@1.1-13 r-tnet@3.0.16 r-selectboost@2.3.0 r-plotrix@3.8-13 r-nnls@1.6 r-movmf@0.2-9 r-mfuzz@2.70.0 r-limma@3.66.0 r-lattice@0.22-7 r-lars@1.3 r-igraph@2.2.1 r-gplots@3.2.0 r-e1071@1.7-16 r-cluster@2.1.8.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://fbertran.github.io/Patterns/
Licenses: GPL 2+
Build system: r
Synopsis: Deciphering Biological Networks with Patterned Heterogeneous Measurements
Description:

This package provides a modeling tool dedicated to biological network modeling (Bertrand and others 2020, <doi:10.1093/bioinformatics/btaa855>). It allows for single or joint modeling of, for instance, genes and proteins. It starts with the selection of the actors that will be the used in the reverse engineering upcoming step. An actor can be included in that selection based on its differential measurement (for instance gene expression or protein abundance) or on its time course profile. Wrappers for actors clustering functions and cluster analysis are provided. It also allows reverse engineering of biological networks taking into account the observed time course patterns of the actors. Many inference functions are provided and dedicated to get specific features for the inferred network such as sparsity, robust links, high confidence links or stable through resampling links. Some simulation and prediction tools are also available for cascade networks (Jung and others 2014, <doi:10.1093/bioinformatics/btt705>). Example of use with microarray or RNA-Seq data are provided.

r-pdindex 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PDIndex
Licenses: GPL 3
Build system: r
Synopsis: Disease Intensity and Progress Curve Indices for Plant Pathology
Description:

This package provides standardised functions for quantifying plant disease intensity and disease development over time. The package implements Percent Disease Index (PDI) for assessing overall disease severity based on categorical ratings, Area Under the Disease Progress Curve (AUDPC) for summarizing disease progression using trapezoidal integration, and Relative AUDPC (rAUDPC) for expressing disease development relative to the maximum possible severity over the observation period. These indices are widely used in plant pathology and epidemiology for comparing treatments, cultivars, and environments.

r-pcredux 1.2-1
Propagated dependencies: r-zoo@1.8-14 r-shiny@1.11.1 r-segmented@2.1-4 r-robustbase@0.99-6 r-qpcr@1.4-2 r-pracma@2.4.6 r-pbapply@1.7-4 r-mbmca@1.1-0 r-fda-usc@2.2.0 r-ecp@3.1.6 r-chippcr@1.0-2 r-changepoint@2.3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://CRAN.R-project.org/package=PCRedux
Licenses: Expat
Build system: r
Synopsis: Quantitative Polymerase Chain Reaction (qPCR) Data Mining and Machine Learning Toolkit as Described in Burdukiewicz (2022) <doi:10.21105/Joss.04407>
Description:

Extracts features from amplification curve data of quantitative Polymerase Chain Reactions (qPCR) according to Pabinger et al. 2014 <doi:10.1016/j.bdq.2014.08.002> for machine learning purposes. Helper functions prepare the amplification curve data for processing as functional data (e.g., Hausdorff distance) or enable the plotting of amplification curve classes (negative, ambiguous, positive). The hookreg() and hookregNL() functions of Burdukiewicz et al. (2018) <doi:10.1016/j.bdq.2018.08.001> can be used to predict amplification curves with an hook effect-like curvature. The pcrfit_single() function can be used to extract features from an amplification curve.

r-plsdepot 0.3.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/gastonstat/plsdepot/
Licenses: GPL 3
Build system: r
Synopsis: Partial Least Squares (PLS) Data Analysis Methods
Description:

Different methods for PLS analysis of one or two data tables such as Tucker's Inter-Battery, NIPALS, SIMPLS, SIMPLS-CA, PLS Regression, and PLS Canonical Analysis. The main reference for this software is the awesome book (in French) La Regression PLS: Theorie et Pratique by Michel Tenenhaus.

r-pugmm 0.1.2
Propagated dependencies: r-rcpp@1.1.0 r-ppclust@1.1.0.1 r-mcompanion@0.6 r-mclust@6.1.2 r-matrix@1.7-4 r-mass@7.3-65 r-manlymix@0.1.15.1 r-igraph@2.2.1 r-foreach@1.5.2 r-doparallel@1.0.17 r-clusterr@1.3.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/giorgiazaccaria/PUGMM
Licenses: Expat
Build system: r
Synopsis: Parsimonious Ultrametric Gaussian Mixture Models
Description:

Parsimonious Ultrametric Gaussian Mixture Models via grouped coordinate ascent (equivalent to EM) algorithm characterized by the inspection of hierarchical relationships among variables via parsimonious extended ultrametric covariance structures. The methodologies are described in Cavicchia, Vichi, Zaccaria (2024) <doi:10.1007/s11222-024-10405-9>, (2022) <doi:10.1007/s11634-021-00488-x> and (2020) <doi:10.1007/s11634-020-00400-z>.

r-psycho 0.6.1
Propagated dependencies: r-stringr@1.6.0 r-scales@1.4.0 r-parameters@0.28.3 r-insight@1.4.3 r-ggplot2@4.0.1 r-effectsize@1.0.1 r-dplyr@1.1.4 r-bayestestr@0.17.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/neuropsychology/psycho.R
Licenses: Expat
Build system: r
Synopsis: Efficient and Publishing-Oriented Workflow for Psychological Science
Description:

The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, to facilitate and speed up the time spent on data analysis. It aims at supporting best practices and tools to format the output of statistical methods to directly paste them into a manuscript, ensuring statistical reporting standardization and conformity.

r-pssmooth 1.0.3
Propagated dependencies: r-osdesign@1.8 r-np@0.60-18 r-mass@7.3-65 r-chngpt@2024.11-15
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/mjuraska/pssmooth
Licenses: GPL 2
Build system: r
Synopsis: Flexible and Efficient Evaluation of Principal Surrogates/Treatment Effect Modifiers
Description:

This package implements estimation and testing procedures for evaluating an intermediate biomarker response as a principal surrogate of a clinical response to treatment (i.e., principal stratification effect modification analysis), as described in Juraska M, Huang Y, and Gilbert PB (2020), Inference on treatment effect modification by biomarker response in a three-phase sampling design, Biostatistics, 21(3): 545-560 <doi:10.1093/biostatistics/kxy074>. The methods avoid the restrictive placebo structural risk modeling assumption common to past methods and further improve robustness by the use of nonparametric kernel smoothing for biomarker density estimation. A randomized controlled two-group clinical efficacy trial is assumed with an ordered categorical or continuous univariate biomarker response measured at a fixed timepoint post-randomization and with a univariate baseline surrogate measure allowed to be observed in only a subset of trial participants with an observed biomarker response (see the flexible three-phase sampling design in the paper for details). Bootstrap-based procedures are available for pointwise and simultaneous confidence intervals and testing of four relevant hypotheses. Summary and plotting functions are provided for estimation results.

r-plavaan 0.0.1
Propagated dependencies: r-numderiv@2016.8-1.1 r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://marklhc.github.io/plavaan/
Licenses: Expat
Build system: r
Synopsis: Penalized Estimation for Latent Variable Models with 'lavaan'
Description:

Extends the popular lavaan package by adding penalized estimation capabilities. It supports penalty on individual parameters as well as the difference between parameters.

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