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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-powriclpm 0.2.1
Propagated dependencies: r-rlang@1.1.6 r-progressr@0.18.0 r-lifecycle@1.0.4 r-lavaan@0.6-20 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-future@1.68.0 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://jeroendmulder.github.io/powRICLPM/
Licenses: Expat
Build system: r
Synopsis: Perform Power Analysis for the RI-CLPM and STARTS Model
Description:

Perform user-friendly power analyses for the random intercept cross-lagged panel model (RI-CLPM) and the bivariate stable trait autoregressive trait state (STARTS) model. The strategy as proposed by Mulder (2023) <doi:10.1080/10705511.2022.2122467> is implemented. Extensions include the use of parameter constraints over time, bounded estimation, generation of data with skewness and kurtosis, and the option to setup the power analysis for Mplus.

r-poolhelper 1.1.0
Propagated dependencies: r-scrm@1.7.5 r-metrics@0.1.4 r-mcmcpack@1.7-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/joao-mcarvalho/poolHelper
Licenses: GPL 3+
Build system: r
Synopsis: Simulates Pooled Sequencing Genetic Data
Description:

Simulates pooled sequencing data under a variety of conditions. Also allows for the evaluation of the average absolute difference between allele frequencies computed from genotypes and those computed from pooled data. Carvalho et al., (2022) <doi:10.1101/2023.01.20.524733>.

r-priorgen 2.0
Propagated dependencies: r-rootsolve@1.8.2.4 r-nleqslv@3.3.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PriorGen
Licenses: GPL 3+
Build system: r
Synopsis: Generates Prior Distributions for Proportions
Description:

Translates beliefs into prior information in the form of Beta and Gamma distributions. It can be used for the generation of priors on the prevalence of disease and the sensitivity/specificity of diagnostic tests and any other binomial experiment.

r-prf 1.2
Propagated dependencies: r-reshape2@1.4.5 r-randomforest@4.7-1.2 r-permute@0.9-8 r-multtest@2.66.0 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://cran.r-project.org/package=pRF
Licenses: GPL 3
Build system: r
Synopsis: Permutation Significance for Random Forests
Description:

Estimate False Discovery Rates (FDRs) for importance metrics from random forest runs.

r-poolbal 0.1-0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PoolBal
Licenses: GPL 3+
Build system: r
Synopsis: Balancing Central and Marginal Rejection of Pooled p-Values
Description:

When using pooled p-values to adjust for multiple testing, there is an inherent balance that must be struck between rejection based on weak evidence spread among many tests and strong evidence in a few, explored in Salahub and Olford (2023) <arXiv:2310.16600>. This package provides functionality to compute marginal and central rejection levels and the centrality quotient for p-value pooling functions and provides implementations of the chi-squared quantile pooled p-value (described in Salahub and Oldford (2023)) and a proposal from Heard and Rubin-Delanchy (2018) <doi:10.1093/biomet/asx076> to control the quotient's value.

r-pbr 0.0.2
Propagated dependencies: r-leaflet@2.2.3 r-jsonlite@2.0.0 r-httr@1.4.7 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pbr
Licenses: Expat
Build system: r
Synopsis: Find a Cold One Near You
Description:

In short, this package is a locator for cool, refreshing beverages. It will find and return the nearest location where you can get a cold one.

r-plsrcox 1.8.0
Propagated dependencies: r-survival@3.8-3 r-survcomp@1.60.0 r-survauc@1.4-0 r-rms@8.1-0 r-risksetroc@1.0.4.1 r-plsrglm@1.6.0 r-pls@2.8-5 r-mixomics@6.34.0 r-lars@1.3 r-kernlab@0.9-33
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://fbertran.github.io/plsRcox/
Licenses: GPL 3
Build system: r
Synopsis: Partial Least Squares Regression for Cox Models and Related Techniques
Description:

This package provides Partial least squares Regression and various regular, sparse or kernel, techniques for fitting Cox models in high dimensional settings <doi:10.1093/bioinformatics/btu660>, Bastien, P., Bertrand, F., Meyer N., Maumy-Bertrand, M. (2015), Deviance residuals-based sparse PLS and sparse kernel PLS regression for censored data, Bioinformatics, 31(3):397-404. Cross validation criteria were studied in <doi:10.48550/arXiv.1810.02962>, Bertrand, F., Bastien, Ph. and Maumy-Bertrand, M. (2018), Cross validating extensions of kernel, sparse or regular partial least squares regression models to censored data.

r-plnmodels 1.2.2
Propagated dependencies: r-torch@0.16.3 r-tidyr@1.3.1 r-scales@1.4.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-r6@2.6.1 r-purrr@1.2.0 r-pscl@1.5.9 r-nloptr@2.2.1 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-igraph@2.2.1 r-gridextra@2.3 r-glassofast@1.0.1 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-future@1.68.0 r-dplyr@1.1.4 r-corrplot@0.95 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://pln-team.github.io/PLNmodels/
Licenses: GPL 3+
Build system: r
Synopsis: Poisson Lognormal Models
Description:

The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin, 2021 <doi:10.3389/fevo.2021.588292>) can be used for a variety of multivariate problems when count data are at play, including principal component analysis for count data, discriminant analysis, model-based clustering and network inference. Implements variational algorithms to fit such models accompanied with a set of functions for visualization and diagnostic.

r-posetr 1.1.4
Propagated dependencies: r-rdpack@2.6.4 r-rcpp@1.1.0 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=POSetR
Licenses: GPL 2+
Build system: r
Synopsis: Partially Ordered Sets in R
Description:

This package provides a set of basic tools for generating, analyzing, summarizing and visualizing finite partially ordered sets. In particular, it implements flexible and very efficient algorithms for the extraction of linear extensions and for the computation of mutual ranking probabilities and other user-defined functionals, over them. The package is meant as a computationally efficient "engine", for the implementation of data analysis procedures, on systems of multidimensional ordinal indicators and partially ordered data, in the spirit of Fattore, M. (2016) "Partially ordered sets and the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-015-1059-6>, and Fattore M. and Arcagni, A. (2018) "A reduced posetic approach to the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-016-1501-4>.

r-pkdata 0.1.0
Propagated dependencies: r-lubridate@1.9.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pkdata
Licenses: GPL 3+
Build system: r
Synopsis: Creates Pharmacokinetic/Pharmacodynamic (PK/PD) Data
Description:

Prepare pharmacokinetic/pharmacodynamic (PK/PD) data for PK/PD analyses. This package provides functions to standardize infusion and bolus dose data while linking it to drug level or concentration data.

r-poly4at 1.0.1
Propagated dependencies: r-shinydashboard@0.7.3 r-shiny@1.11.1 r-sf@1.0-23 r-readxl@1.4.5 r-leaflet-extras@2.0.1 r-leaflet@2.2.3 r-jsonlite@2.0.0 r-httr@1.4.7 r-geojsonsf@2.0.5 r-dt@0.34.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/farmse988/Poly4AT
Licenses: Expat
Build system: r
Synopsis: Access 'INVEKOS' API for Field Polygons
Description:

This package provides a shiny app that allows to access and use the INVEKOS API for field polygons in Austria. API documentation is available at <https://gis.lfrz.gv.at/api/geodata/i009501/ogc/features/v1/>.

r-provparser 1.0
Propagated dependencies: r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/End-to-end-provenance
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Pulls Information from Prov.Json Files
Description:

R functions to access provenance information collected by rdt or rdtLite'. The information is stored inside a ProvInfo object and can be accessed through a collection of functions that will return the requested data. The exact format of the JSON created by rdt and rdtLite is described in <https://github.com/End-to-end-provenance/ExtendedProvJson>.

r-proteinpca 0.1.1
Propagated dependencies: r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ProteinPCA
Licenses: GPL 3
Build system: r
Synopsis: Principal Component Analysis (PCA) Tool on Protein Expression Data
Description:

Analysis of protein expression data can be done through Principal Component Analysis (PCA), and this R package is designed to streamline the analysis. This package enables users to perform PCA and it generates biplot and scree plot for advanced graphical visualization. Optionally, it supports grouping/clustering visualization with PCA loadings and confidence ellipses. With this R package, researchers can quickly explore complex protein datasets, interpret variance contributions, and visualize sample clustering through intuitive biplots. For more details, see Jolliffe (2001) <doi:10.1007/b98835>, Gabriel (1971) <doi:10.1093/biomet/58.3.453>, Zhang et al. (2024) <doi:10.1038/s41467-024-53239-9>, and Anandan et al. (2022) <doi:10.1038/s41598-022-07781-5>.

r-pikchr 1.0.3
Propagated dependencies: r-stringr@1.6.0 r-rsvg@2.7.0 r-rlang@1.1.6 r-purrr@1.2.0 r-knitr@1.50 r-htmltools@0.5.8.1 r-dplyr@1.1.4 r-brio@1.1.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: <https://github.com/StrategicProjects/pikchr>
Licenses: GPL 2+
Build system: r
Synopsis: R Wrapper for 'pikchr' (PIC) Diagram Language
Description:

An R interface to pikchr (<https://pikchr.org>, pronounced â pictureâ ), a PIC'-like markup language for creating diagrams within technical documentation. Originally developed by Brian Kernighan, PIC has been adapted into pikchr by D. Richard Hipp, the creator of SQLite'. pikchr is designed to be embedded in fenced code blocks of Markdown or other documentation markup languages, making it ideal for generating diagrams in text-based formats. This package allows R users to seamlessly integrate the descriptive syntax of pikchr for diagram creation directly within the R environment.

r-pjfm 0.1.0
Propagated dependencies: r-survival@3.8-3 r-statmod@1.5.1 r-rcppensmallen@0.3.10.0.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PJFM
Licenses: GPL 2
Build system: r
Synopsis: Variational Inference for High-Dimensional Joint Frailty Model
Description:

Joint frailty models have been widely used to study the associations between recurrent events and a survival outcome. However, existing joint frailty models only consider one or a few recurrent events and cannot deal with high-dimensional recurrent events. This package can be used to fit our recently developed penalized joint frailty model that can handle high-dimensional recurrent events. Specifically, an adaptive lasso penalty is imposed on the parameters for the effects of the recurrent events on the survival outcome, which allows for variable selection. Also, our algorithm is computationally efficient, which is based on the Gaussian variational approximation method.

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-personalized 0.2.8
Propagated dependencies: r-xgboost@1.7.11.1 r-survival@3.8-3 r-plotly@4.11.0 r-mgcv@1.9-4 r-kernlab@0.9-33 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-foreach@1.5.2 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://jaredhuling.org/personalized/
Licenses: GPL 2
Build system: r
Synopsis: Estimation and Validation Methods for Subgroup Identification and Personalized Medicine
Description:

This package provides functions for fitting and validation of models for subgroup identification and personalized medicine / precision medicine under the general subgroup identification framework of Chen et al. (2017) <doi:10.1111/biom.12676>. This package is intended for use for both randomized controlled trials and observational studies and is described in detail in Huling and Yu (2021) <doi:10.18637/jss.v098.i05>.

r-phylometrics 0.0.1
Propagated dependencies: r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=phylometrics
Licenses: GPL 2+
Build system: r
Synopsis: Estimating Statistical Errors of Phylogenetic Metrics
Description:

This package provides functions to estimate statistical errors of phylogenetic metrics particularly to detect binary trait influence on diversification, as well as a function to simulate trees with fixed number of sampled taxa and trait prevalence.

r-portfolio 0.5-3
Propagated dependencies: r-nlme@3.1-168 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/dgerlanc/portfolio
Licenses: GPL 2+
Build system: r
Synopsis: Analysing Equity Portfolios
Description:

This package provides classes for analysing and implementing equity portfolios, including routines for generating tradelists and calculating exposures to user-specified risk factors.

r-practicalsigni 0.1.2
Propagated dependencies: r-xtable@1.8-4 r-shapleyvalue@0.2.0 r-randomforest@4.7-1.2 r-np@0.60-18 r-nns@11.6.4 r-hypergeo@1.2-14 r-generalcorr@1.2.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=practicalSigni
Licenses: GPL 2+
Build system: r
Synopsis: Practical Significance Ranking of Regressors and Exact t Density
Description:

Consider a possibly nonlinear nonparametric regression with p regressors. We provide evaluations by 13 methods to rank regressors by their practical significance or importance using various methods, including machine learning tools. Comprehensive methods are as follows. m6=Generalized partial correlation coefficient or GPCC by Vinod (2021)<doi:10.1007/s10614-021-10190-x> and Vinod (2022)<https://www.mdpi.com/1911-8074/15/1/32>. m7= a generalization of psychologists effect size incorporating nonlinearity and many variables. m8= local linear partial (dy/dxi) using the np package for kernel regressions. m9= partial (dy/dxi) using the NNS package. m10= importance measure using the NNS boost function. m11= Shapley Value measure of importance (cooperative game theory). m12 and m13= two versions of the random forest algorithm. Taraldsen's exact density for sampling distribution of correlations added.

r-paleomorph 0.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/timcdlucas/paleomorph/
Licenses: Expat
Build system: r
Synopsis: Geometric Morphometric Tools for Paleobiology
Description:

Fill missing symmetrical data with mirroring, calculate Procrustes alignments with or without scaling, and compute standard or vector correlation and covariance matrices (congruence coefficients) of 3D landmarks. Tolerates missing data for all analyses.

r-partsm 1.1-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/MatthieuStigler/partsm
Licenses: GPL 2
Build system: r
Synopsis: Periodic Autoregressive Time Series Models
Description:

Basic functions to fit and predict periodic autoregressive time series models. These models are discussed in the book P.H. Franses (1996) "Periodicity and Stochastic Trends in Economic Time Series", Oxford University Press. Data set analyzed in that book is also provided. NOTE: the package was orphaned during several years. It is now only maintained, but no major enhancements are expected, and the maintainer cannot provide any support.

r-psindependencetest 0.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PSIndependenceTest
Licenses: GPL 3
Build system: r
Synopsis: Independence Tests for Two-Way, Three-Way and Four-Way Contingency Tables
Description:

Presentation two independence tests for two-way, three-way and four-way contingency tables. These tests are: the modular test and the logarithmic minimum test. For details on this method see: Sulewski (2017) <doi:10.18778/0208-6018.330.04>, Sulewski (2018) <doi:10.1080/02664763.2018.1424122>, Sulewski (2019) <doi:10.2478/bile-2019-0003>, Sulewski (2021) <doi:10.1080/00949655.2021.1908286>.

r-pwepred 1.0.0
Propagated dependencies: r-survival@3.8-3 r-segmented@2.1-4 r-foreach@1.5.2 r-fastmatch@1.1-6 r-dosnow@1.0.20
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PwePred
Licenses: Expat
Build system: r
Synopsis: Event/Timeline Prediction Model Based on Piecewise Exponential
Description:

Efficient algorithm for estimating piecewise exponential hazard models for right-censored data, and is useful for reliable power calculation, study design, and event/timeline prediction for study monitoring.

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