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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-periodics 0.5.0
Propagated dependencies: r-rms@8.1-0 r-hmisc@5.2-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=peRiodiCS
Licenses: GPL 3
Build system: r
Synopsis: Functions for Generating Periodic Curves
Description:

This package provides functions for generating variants of curves: restricted cubic spline, periodic restricted cubic spline, periodic cubic spline. Periodic splines can be used to model data that has periodic nature / seasonality.

r-pathmodelfit 1.0.5
Propagated dependencies: r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pathmodelfit
Licenses: GPL 3
Build system: r
Synopsis: Path Component Fit Indices for Latent Structural Equation Models
Description:

This package provides functions for computing fit indices for evaluating the path component of latent variable structural equation models. Available fit indices include RMSEA-P and NSCI-P originally presented and evaluated by Williams and O'Boyle (2011) <doi:10.1177/1094428110391472> and demonstrated by O'Boyle and Williams (2011) <doi:10.1037/a0020539> and Williams, O'Boyle, & Yu (2020) <doi:10.1177/1094428117736137>. Also included are fit indices described by Hancock and Mueller (2011) <doi:10.1177/0013164410384856>.

r-plsmselect 0.2.0
Propagated dependencies: r-survival@3.8-3 r-mgcv@1.9-4 r-glmnet@4.1-10 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=plsmselect
Licenses: GPL 2
Build system: r
Synopsis: Linear and Smooth Predictor Modelling with Penalisation and Variable Selection
Description:

Fit a model with potentially many linear and smooth predictors. Interaction effects can also be quantified. Variable selection is done using penalisation. For l1-type penalties we use iterative steps alternating between using linear predictors (lasso) and smooth predictors (generalised additive model).

r-poet 2.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=POET
Licenses: GPL 2
Build system: r
Synopsis: Principal Orthogonal ComplEment Thresholding (POET) Method
Description:

Estimate large covariance matrices in approximate factor models by thresholding principal orthogonal complements.

r-pwrfdr 3.2.4
Propagated dependencies: r-tablemonster@1.7.8 r-stringr@1.6.0 r-mvtnorm@1.3-3 r-ggplot2@4.0.1 r-flextable@0.9.10
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pwrFDR
Licenses: GPL 2+
Build system: r
Synopsis: FDR Power
Description:

Computing Average and TPX Power under various BHFDR type sequential procedures. All of these procedures involve control of some summary of the distribution of the FDP, e.g. the proportion of discoveries which are false in a given experiment. The most widely known of these, the BH-FDR procedure, controls the FDR which is the mean of the FDP. A lesser known procedure, due to Lehmann and Romano, controls the FDX, or probability that the FDP exceeds a user provided threshold. This is less conservative than FWE control procedures but much more conservative than the BH-FDR proceudre. This package and the references supporting it introduce a new procedure for controlling the FDX which we call the BH-FDX procedure. This procedure iteratively identifies, given alpha and lower threshold delta, an alpha* less than alpha at which BH-FDR guarantees FDX control. This uses asymptotic approximation and is only slightly more conservative than the BH-FDR procedure. Likewise, we can think of the power in multiple testing experiments in terms of a summary of the distribution of the True Positive Proportion (TPP), the portion of tests truly non-null distributed that are called significant. The package will compute power, sample size or any other missing parameter required for power defined as (i) the mean of the TPP (average power) or (ii) the probability that the TPP exceeds a given value, lambda, (TPX power) via asymptotic approximation. All supplied theoretical results are also obtainable via simulation. The suggested approach is to narrow in on a design via the theoretical approaches and then make final adjustments/verify the results by simulation. The theoretical results are described in Izmirlian, G (2020) Statistics and Probability letters, "<doi:10.1016/j.spl.2020.108713>", and an applied paper describing the methodology with a simulation study is in preparation. See citation("pwrFDR").

r-personalized2part 0.0.2
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-personalized@0.2.8 r-hdtweedie@1.2 r-foreach@1.5.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/jaredhuling/personalized2part
Licenses: GPL 2+
Build system: r
Synopsis: Two-Part Estimation of Treatment Rules for Semi-Continuous Data
Description:

This package implements the methodology of Huling, Smith, and Chen (2020) <doi:10.1080/01621459.2020.1801449>, which allows for subgroup identification for semi-continuous outcomes by estimating individualized treatment rules. It uses a two-part modeling framework to handle semi-continuous data by separately modeling the positive part of the outcome and an indicator of whether each outcome is positive, but still results in a single treatment rule. High dimensional data is handled with a cooperative lasso penalty, which encourages the coefficients in the two models to have the same sign.

r-panjen 1.6
Propagated dependencies: r-mgcv@1.9-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PanJen
Licenses: GPL 2+
Build system: r
Synopsis: Semi-Parametric Test for Specifying Functional Form
Description:

This package provides a central decision in a parametric regression is how to specify the relation between an dependent variable and each explanatory variable. This package provides a semi-parametric tool for comparing different transformations of an explanatory variables in a parametric regression. The functions is relevant in a situation, where you would use a box-cox or Box-Tidwell transformations. In contrast to the classic power-transformations, the methods in this package allows for theoretical driven user input and the possibility to compare with a non-parametric transformation.

r-pkgdepr 1.1.1
Propagated dependencies: r-visnetwork@2.1.4 r-viridislite@0.4.2 r-scales@1.4.0 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://pkgdepR.org/
Licenses: Expat
Build system: r
Synopsis: Statically Determine Function Dependencies Between Packages
Description:

Statically determine and visualize the function dependencies within and across packages. This may be useful for managing function dependencies across a code base of multiple R packages.

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-pasadr 1.0
Propagated dependencies: r-scales@1.4.0 r-pracma@2.4.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/ainsuotain/pasadr
Licenses: GPL 3
Build system: r
Synopsis: An Implementation of Process-Aware Stealthy Attack Detection(PASAD)
Description:

Anomaly detection method based on the paper "Truth will out: Departure-based process-level detection of stealthy attacks on control systems" from Wissam Aoudi, Mikel Iturbe, and Magnus Almgren (2018) <DOI:10.1145/3243734.3243781>. Also referred to the following implementation: <https://github.com/rahulrajpl/PyPASAD>.

r-pss-health 1.1.5
Propagated dependencies: r-writexl@1.5.4 r-shinyhelper@0.3.2 r-shinyfeedback@0.4.0 r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-pwr2@1.0 r-pwr@1.3-0 r-proc@1.19.0.1 r-presize@0.3.9 r-powersurvepi@0.1.5 r-powermediation@0.3.4 r-plotly@4.11.0 r-longpower@1.0.27 r-kappasize@1.2 r-icc-sample-size@1.0 r-ggplot2@4.0.1 r-epir@2.0.91 r-envstats@3.1.0 r-easypower@1.0.2 r-dt@0.34.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/
Licenses: GPL 2+
Build system: r
Synopsis: Power and Sample Size for Health Researchers via Shiny
Description:

Power and Sample Size for Health Researchers is a Shiny application that brings together a series of functions related to sample size and power calculations for common analysis in the healthcare field. There are functionalities to calculate the power, sample size to estimate or test hypotheses for means and proportions (including test for correlated groups, equivalence, non-inferiority and superiority), association, correlations coefficients, regression coefficients (linear, logistic, gamma, and Cox), linear mixed model, Cronbach's alpha, interobserver agreement, intraclass correlation coefficients, limit of agreement on Bland-Altman plots, area under the curve, sensitivity and specificity incorporating the prevalence of disease. You can also use the online version at <https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/>.

r-proliferativeindex 1.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ProliferativeIndex
Licenses: Expat
Build system: r
Synopsis: Calculates and Analyzes the Proliferative Index
Description:

This package provides functions for calculating and analyzing the proliferative index (PI) from an RNA-seq dataset. As described in Ramaker & Lasseigne, et al. bioRxiv, 2016 <doi:10.1101/063057>.

r-planetnicfi 1.0.5
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-httr@1.4.7 r-glue@1.8.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/mlampros/PlanetNICFI
Licenses: GPL 3
Build system: r
Synopsis: Processing of the 'Planet NICFI' Satellite Imagery
Description:

It includes functions to download and process the Planet NICFI (Norway's International Climate and Forest Initiative) Satellite Imagery utilizing the Planet Mosaics API <https://developers.planet.com/docs/basemaps/reference/#tag/Basemaps-and-Mosaics>. GDAL (library for raster and vector geospatial data formats) and aria2c (paralleled download utility) must be installed and configured in the user's Operating System.

r-plan 0.4-5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/dankelley/plan
Licenses: GPL 2+
Build system: r
Synopsis: Tools for Project Planning
Description:

Supports the creation of burndown charts and gantt diagrams.

r-precisesums 0.7
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/nlmixr2/PreciseSums
Licenses: GPL 2+
Build system: r
Synopsis: Accurate Floating Point Sums and Products
Description:

Most of the time floating point arithmetic does approximately the right thing. When adding sums or having products of numbers that greatly differ in magnitude, the floating point arithmetic may be incorrect. This package implements the Kahan (1965) sum <doi:10.1145/363707.363723>, Neumaier (1974) sum <doi:10.1002/zamm.19740540106>, pairwise-sum (adapted from NumPy', See Castaldo (2008) <doi:10.1137/070679946> for a discussion of accuracy), and arbitrary precision sum (adapted from the fsum in Python ; Shewchuk (1997) <https://people.eecs.berkeley.edu/~jrs/papers/robustr.pdf>). In addition, products are changed to long double precision for accuracy, or changed into a log-sum for accuracy.

r-pez 1.2-5
Propagated dependencies: r-vegan@2.7-2 r-quantreg@6.1 r-picante@1.8.2 r-phytools@2.5-2 r-mvtnorm@1.3-3 r-matrix@1.7-4 r-fd@1.0-12.3 r-caper@1.0.4 r-ape@5.8-1 r-animation@2.8 r-ade4@1.7-23
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pez
Licenses: GPL 3
Build system: r
Synopsis: Phylogenetics for the Environmental Sciences
Description:

Eco-phylogenetic and community phylogenetic analyses. Keeps community ecological and phylogenetic data matched up and comparable using comparative.comm objects. Wrappers for common community phylogenetic indices ('pez.shape', pez.evenness', pez.dispersion', and pez.dissimilarity metrics). Implementation of Cavender-Bares (2004) correlation of phylogenetic and ecological matrices ('fingerprint.regression'). Phylogenetic Generalised Linear Mixed Models (PGLMMs; pglmm') following Ives & Helmus (2011) and Rafferty & Ives (2013). Simulation of null assemblages, traits, and phylogenies ('scape', sim.meta.comm').

r-purpleairapi 0.1.0
Propagated dependencies: r-jsonlite@2.0.0 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/heba-razzak/PurpleAirAPI
Licenses: Expat
Build system: r
Synopsis: Historical Data Retrieval from 'PurpleAir' Sensors via API
Description:

This package provides tools for retrieving and analyzing air quality data from PurpleAir sensors through their API. Functions enable downloading historical measurements, accessing sensor metadata, and managing API request limitations through chunked data retrieval. For more information about the PurpleAir API, see <https://api.purpleair.com/>.

r-piecepackr 1.15.3
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-r6@2.6.1 r-purrr@1.2.0 r-png@0.1-8 r-jpeg@0.1-11 r-grimport2@0.3-3 r-gridgeometry@0.4-0 r-affiner@0.2.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://trevorldavis.com/piecepackr/
Licenses: Expat
Build system: r
Synopsis: Board Game Graphics
Description:

This package provides functions to make board game graphics with the ggplot2', grid', rayrender', rayvertex', and rgl packages. Specializes in game diagrams, animations, and "Print & Play" layouts for the piecepack <https://www.ludism.org/ppwiki> but can make graphics for other board game systems. Includes configurations for several public domain game systems such as checkers, (double-18) dominoes, go, piecepack', playing cards, etc.

r-phenmodel 1.0
Propagated dependencies: r-reshape@0.8.10 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=phenModel
Licenses: GPL 2+
Build system: r
Synopsis: Insect Phenology Model Evaluation Based on Daily Temperatures
Description:

Generates predicted stage change days for an insect, based on daily temperatures and development rate parameters, as developed by Pollard (2014) <http://mural.maynoothuniversity.ie/view/ethesisauthor/Pollard=3ACiaran_P=2E=3A=3A.html>. A few example datasets are included and implemented for P. vulgatissima, the blue willow beetle, but the approach can be readily applied to other species that display similar behaviour.

r-parafac4microbiome 1.3.2
Propagated dependencies: r-tidyr@1.3.1 r-rtensor@1.4.9 r-rlang@1.1.6 r-pracma@2.4.6 r-multiway@1.0-7 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-cowplot@1.2.0 r-compositions@2.0-9
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://grvanderploeg.com/parafac4microbiome/
Licenses: Expat
Build system: r
Synopsis: Parallel Factor Analysis Modelling of Longitudinal Microbiome Data
Description:

Creation and selection of PARAllel FACtor Analysis (PARAFAC) models of longitudinal microbiome data. You can import your own data with our import functions or use one of the example datasets to create your own PARAFAC models. Selection of the optimal number of components can be done using assessModelQuality() and assessModelStability(). The selected model can then be plotted using plotPARAFACmodel(). The Parallel Factor Analysis method was originally described by Caroll and Chang (1970) <doi:10.1007/BF02310791> and Harshman (1970) <https://www.psychology.uwo.ca/faculty/harshman/wpppfac0.pdf>.

r-probaverse 0.1.0
Propagated dependencies: r-famish@0.2.0 r-distplyr@0.2.0 r-distionary@0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://probaverse.probaverse.com/
Licenses: Expat
Build system: r
Synopsis: Install and Load the 'probaverse' Packages
Description:

The probaverse is a suite of packages designed to facilitate creating advanced statistical models through probability distributions. These packages work best when loaded together because they share a common design philosophy and focus on different aspects of developing statistical models. Inspired by the tidyverse package, the probaverse package makes it easy to load the entire suite of probaverse packages together.

r-portes 6.0
Propagated dependencies: r-vars@1.6-1 r-forecast@8.24.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=portes
Licenses: GPL 2+
Build system: r
Synopsis: Portmanteau Tests for Time Series Models
Description:

This package contains common univariate and multivariate portmanteau test statistics for time series models. These tests are based on using asymptotic distributions such as chi-square distribution and based on using the Monte Carlo significance tests. Also, it can be used to simulate from univariate and multivariate seasonal time series models.

r-populationgrowthr 0.1.1
Propagated dependencies: 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=PopulationGrowthR
Licenses: GPL 3
Build system: r
Synopsis: Linear Population Growth Scenarios
Description:

Fit linear splines to species time series to detect population growth scenarios based on Hyndman, R J and Mesgaran, M B and Cousens, R D (2015) <doi:10.1007/s10530-015-0962-8>.

r-poolvim 1.0.0
Propagated dependencies: r-ranger@0.17.0 r-hmisc@5.2-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=poolVIM
Licenses: GPL 2+
Build system: r
Synopsis: Gene-Based Association Tests using the Actual Impurity Reduction (AIR) Variable Importance
Description:

Gene-based association tests using the actual impurity reduction (AIR) variable importance. The function aggregates AIR importance measures from a group of SNPs or probes and outputs a p-value for each gene. The procedures builds upon the method described in <doi:10.1093/Bioinformatics/Bty373> and will be published soon.

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