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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-pmledecon 0.2.1
Propagated dependencies: r-splitstackshape@1.4.8 r-rmutil@1.1.10
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pmledecon
Licenses: GPL 3+
Build system: r
Synopsis: Deconvolution Density Estimation using Penalized MLE
Description:

Given a sample with additive measurement error, the package estimates the deconvolution density - that is, the density of the underlying distribution of the sample without measurement error. The method maximises the log-likelihood of the estimated density, plus a quadratic smoothness penalty. The distribution of the measurement error can be either a known family, or can be estimated from a "pure error" sample. For known error distributions, the package supports Normal, Laplace or Beta distributed error. For unknown error distribution, a pure error sample independent from the data is used.

r-postdoc 1.4.2
Propagated dependencies: r-xml2@1.5.0 r-prismjs@2.1.0 r-katex@1.5.0 r-jsonlite@2.0.0 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=postdoc
Licenses: Expat
Build system: r
Synopsis: Minimal and Uncluttered Package Documentation
Description:

Generates simple and beautiful one-page HTML reference manuals with package documentation. Math rendering and syntax highlighting are done server-side in R such that no JavaScript libraries are needed in the browser, which makes the documentation portable and fast to load.

r-pylintr 0.1.0
Propagated dependencies: r-rstudioapi@0.17.1 r-htmlwidgets@1.6.4 r-fansi@1.0.7
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/stla/pylintR
Licenses: GPL 3
Build system: r
Synopsis: Lint 'Python' Files with a R Command or a 'RStudio' Addin
Description:

Allow to run pylint on Python files with a R command or a RStudio addin. The report appears in the RStudio viewer pane as a formatted HTML file.

r-profiler 0.3-5
Propagated dependencies: r-reshape@0.8.10 r-rcolorbrewer@1.1-3 r-lavaan@0.6-20 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=profileR
Licenses: GPL 2+
Build system: r
Synopsis: Profile Analysis of Multivariate Data in R
Description:

This package provides a suite of multivariate methods and data visualization tools to implement profile analysis and cross-validation techniques described in Davison & Davenport (2002) <DOI: 10.1037/1082-989X.7.4.468>, Bulut (2013), and other published and unpublished resources. The package includes routines to perform criterion-related profile analysis, profile analysis via multidimensional scaling, moderated profile analysis, profile analysis by group, and a within-person factor model to derive score profiles.

r-portfoliooptim 1.1.1
Propagated dependencies: r-rsymphony@0.1-33
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PortfolioOptim
Licenses: GPL 3
Build system: r
Synopsis: Small/Large Sample Portfolio Optimization
Description:

Two functions for financial portfolio optimization by linear programming are provided. One function implements Benders decomposition algorithm and can be used for very large data sets. The other, applicable for moderate sample sizes, finds optimal portfolio which has the smallest distance to a given benchmark portfolio.

r-procdata 0.3.2
Dependencies: python@3.11.14
Propagated dependencies: r-rcpp@1.1.0 r-keras@2.16.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ProcData
Licenses: GPL 2+
Build system: r
Synopsis: Process Data Analysis
Description:

This package provides tools for exploratory process data analysis. Process data refers to the data describing participants problem-solving processes in computer-based assessments. It is often recorded in computer log files. This package provides functions to read, process, and write process data. It also implements two feature extraction methods to compress the information stored in process data into standard numerical vectors. This package also provides recurrent neural network based models that relate response processes with other binary or scale variables of interest. The functions that involve training and evaluating neural networks are wrappers of functions in keras'.

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.

r-pinstimation 0.2.0
Propagated dependencies: r-tidyr@1.3.1 r-skellam@0.2.4 r-rmarkdown@2.30 r-rdpack@2.6.4 r-nloptr@2.2.1 r-magrittr@2.0.4 r-knitr@1.50 r-future@1.68.0 r-furrr@0.3.1 r-dplyr@1.1.4 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://www.pinstimation.com
Licenses: GPL 3+
Build system: r
Synopsis: Estimation of the Probability of Informed Trading
Description:

This package provides a comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, 2012). Implementations of various estimation methods suggested in the literature are included. Additional compelling features comprise posterior probabilities, an implementation of an expectation-maximization (EM) algorithm, and PIN decomposition into layers, and into bad/good components. Versatile data simulation tools, and trade classification algorithms are among the supplementary utilities. The package provides fast, compact, and precise utilities to tackle the sophisticated, error-prone, and time-consuming estimation procedure of informed trading, and this solely using the raw trade-level data.

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-perms 1.14
Propagated dependencies: r-rdpack@2.6.4 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=perms
Licenses: FreeBSD
Build system: r
Synopsis: Fast Permutation Computation
Description:

This package implements the algorithm of Christensen (2024) <doi:10.1214/22-BA1353> for estimating marginal likelihoods via permutation counting.

r-pdenaivebayes 0.2.9
Propagated dependencies: r-rcppparallel@5.1.11-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-plotly@4.11.0 r-memshare@1.1.0 r-ggplot2@4.0.1 r-databionicswarm@2.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PDEnaiveBayes
Licenses: GPL 3
Build system: r
Synopsis: Plausible Naive Bayes Classifier Using PDE
Description:

This package provides a nonparametric, multicore-capable plausible naive Bayes classifier based on the Pareto density estimation (PDE) featuring a plausible approach to a pitfall in the Bayesian theorem covering low evidence cases. Stier, Q., Hoffmann, J., and Thrun, M.C.: "Classifying with the Fine Structure of Distributions: Leveraging Distributional Information for Robust and Plausible Naive Bayes" (2026), Machine Learning and Knowledge Extraction (MAKE), <DOI:10.3390/make8010013>.

r-pcsinr 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/felixhenninger/PCSinR
Licenses: GPL 3+
Build system: r
Synopsis: Parallel Constraint Satisfaction Networks in R
Description:

Parallel Constraint Satisfaction (PCS) models are an increasingly common class of models in Psychology, with applications to reading and word recognition (McClelland & Rumelhart, 1981), judgment and decision making (Glöckner & Betsch, 2008; Glöckner, Hilbig, & Jekel, 2014), and several other fields (e.g. Read, Vanman, & Miller, 1997). In each of these fields, they provide a quantitative model of psychological phenomena, with precise predictions regarding choice probabilities, decision times, and often the degree of confidence. This package provides the necessary functions to create and simulate basic Parallel Constraint Satisfaction networks within R.

r-pakpmics2018hh 0.1.0
Propagated dependencies: r-tibble@3.3.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/myaseen208/PakPMICS2018hh
Licenses: GPL 2
Build system: r
Synopsis: Multiple Indicator Cluster Survey (MICS) 2017-18 Household Questionnaire Data for Punjab, Pakistan
Description:

This package provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Household questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).

r-paknacc 0.3.0
Propagated dependencies: r-shinydashboardplus@2.0.6 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-rpivottable@0.3.0 r-magrittr@2.0.4 r-htmltools@0.5.8.1 r-dt@0.34.0 r-collapse@2.1.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PakNAcc
Licenses: GPL 3
Build system: r
Synopsis: 'shiny' App for National Accounts
Description:

This package provides a comprehensive suite of tools for analyzing Pakistan's Quarterly National Accounts data. Users can gain detailed insights into Pakistan's economic performance, visualize quarterly trends, and detect patterns and anomalies in key economic indicators. Compare sector contributionsâ including agriculture, industry, and servicesâ to understand their influence on economic growth or decline. Customize analyses by filtering and manipulating data to focus on specific areas of interest. Ideal for policymakers, researchers, and analysts aiming to make informed, data-driven decisions based on timely and detailed economic insights.

r-plotpc 1.0.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: http://www.milbo.users.sonic.net
Licenses: GPL 3
Build system: r
Synopsis: Plot Principal Component Histograms Around a Scatter Plot
Description:

Plot principal component histograms around a bivariate scatter plot.

r-padr 0.6.3
Propagated dependencies: r-rlang@1.1.6 r-rcpp@1.1.0 r-lubridate@1.9.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://edwinth.github.io/padr/
Licenses: Expat
Build system: r
Synopsis: Quickly Get Datetime Data Ready for Analysis
Description:

Transforms datetime data into a format ready for analysis. It offers two core functionalities; aggregating data to a higher level interval (thicken) and imputing records where observations were absent (pad).

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-ppsfs 0.1.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-brglm2@1.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/paradoxical-rhapsody/PPSFS
Licenses: GPL 3
Build system: r
Synopsis: Partial Profile Score Feature Selection in High-Dimensional Generalized Linear Interaction Models
Description:

This is an implementation of the partial profile score feature selection (PPSFS) approach to generalized linear (interaction) models. The PPSFS is highly scalable even for ultra-high-dimensional feature space. See the paper by Xu, Luo and Chen (2022, <doi:10.4310/21-SII706>).

r-presens 2.1.0
Propagated dependencies: r-measurements@1.5.1 r-marelac@2.1.11
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=presens
Licenses: GPL 3
Build system: r
Synopsis: Interface for PreSens Fiber Optic Data
Description:

Makes output files from select PreSens Fiber Optic Oxygen Transmitters easier to work with in R. See <http://www.presens.de> for more information about PreSens (Precision Sensing GmbH). Note: this package is neither created nor maintained by PreSens.

r-purrrlyr 0.0.10
Propagated dependencies: r-rcpp@1.1.0 r-purrr@1.2.0 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://github.com/hadley/purrrlyr
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Tools at the Intersection of 'purrr' and 'dplyr'
Description:

Some functions at the intersection of dplyr and purrr that formerly lived in purrr'.

r-powerlate 0.1.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/kbansak/powerLATE_tutorial
Licenses: GPL 2+
Build system: r
Synopsis: Generalized Power Analysis for LATE
Description:

An implementation of the generalized power analysis for the local average treatment effect (LATE), proposed by Bansak (2020) <doi:10.1214/19-STS732>. Power analysis is in the context of estimating the LATE (also known as the complier average causal effect, or CACE), with calculations based on a test of the null hypothesis that the LATE equals 0 with a two-sided alternative. The method uses standardized effect sizes to place a conservative bound on the power under minimal assumptions. Package allows users to recover power, sample size requirements, or minimum detectable effect sizes. Package also allows users to work with absolute effects rather than effect sizes, to specify an additional assumption to narrow the bounds, and to incorporate covariate adjustment.

r-petests 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PEtests
Licenses: GPL 3+
Build system: r
Synopsis: Power-Enhanced (PE) Tests for High-Dimensional Data
Description:

Two-sample power-enhanced mean tests, covariance tests, and simultaneous tests on mean vectors and covariance matrices for high-dimensional data. Methods of these PE tests are presented in Yu, Li, and Xue (2022) <doi:10.1080/01621459.2022.2126781>; Yu, Li, Xue, and Li (2022) <doi:10.1080/01621459.2022.2061354>.

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-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>.

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Total results: 69112