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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-bsmd 2023.920
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BsMD
Licenses: GPL 3+
Build system: r
Synopsis: Bayes Screening and Model Discrimination
Description:

Bayes screening and model discrimination follow-up designs.

r-bsreg 0.0.2
Propagated dependencies: r-r6@2.6.1 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bsreg
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Bayesian Spatial Regression Models
Description:

Fit Bayesian models with a focus on the spatial econometric models.

r-bincor 0.2.0
Propagated dependencies: r-pracma@2.4.6
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BINCOR
Licenses: GPL 2+
Build system: r
Synopsis: Estimate the Correlation Between Two Irregular Time Series
Description:

Estimate the correlation between two irregular time series that are not necessarily sampled on identical time points. This program is also applicable to the situation of two evenly spaced time series that are not on the same time grid. BINCOR is based on a novel estimation approach proposed by Mudelsee (2010, 2014) to estimate the correlation between two climate time series with different timescales. The idea is that autocorrelation (AR1 process) allows to correlate values obtained on different time points. BINCOR contains four functions: bin_cor() (the main function to build the binned time series), plot_ts() (to plot and compare the irregular and binned time series, cor_ts() (to estimate the correlation between the binned time series) and ccf_ts() (to estimate the cross-correlation between the binned time series).

r-bivgeo 2.1.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://doi.org/10.1285/i20705948v11n1p108
Licenses: GPL 2+
Build system: r
Synopsis: Basu-Dhar Bivariate Geometric Distribution
Description:

This package provides functions to compute the joint probability mass function (pmf), cumulative distribution function (cdf), and survival function (sf) of the Basu-Dhar bivariate geometric distribution. Additional functionalities include the calculation of the correlation coefficient, covariance, and cross-factorial moments, as well as the generation of random variates. The package also implements parameter estimation based on the method of moments.

r-bgdata 2.4.1
Propagated dependencies: r-synchronicity@1.3.10 r-symdmatrix@2.1.1 r-linkedmatrix@1.4.0 r-ff@4.5.2 r-crochet@2.3.0 r-bit@4.6.0 r-bigmemory@4.6.4 r-bedmatrix@2.0.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/QuantGen/BGData
Licenses: Expat
Build system: r
Synopsis: Suite of Packages for Analysis of Big Genomic Data
Description:

An umbrella package providing a phenotype/genotype data structure and scalable and efficient computational methods for large genomic datasets in combination with several other packages: BEDMatrix', LinkedMatrix', and symDMatrix'.

r-bsagri 0.1-10
Propagated dependencies: r-mvtnorm@1.3-3 r-multcomp@1.4-29 r-mratios@1.4.4 r-mcpan@1.1-21 r-gamlss@5.5-0 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BSagri
Licenses: GPL 2
Build system: r
Synopsis: Safety Assessment in Agricultural Field Trials
Description:

Collection of functions, data sets and code examples for evaluations of field trials with the objective of equivalence assessment.

r-bolt4jr 1.4.0
Propagated dependencies: r-reticulate@1.44.1 r-purrr@1.2.0 r-glue@1.8.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bolt4jr
Licenses: Expat
Build system: r
Synopsis: Interface for the 'Neo4j Bolt' Protocol
Description:

Querying, extracting, and processing large-scale network data from Neo4j databases using the Neo4j Bolt <https://neo4j.com/docs/bolt/current/bolt/> protocol. This interface supports efficient data retrieval, batch processing for large datasets, and seamless conversion of query results into R data frames, making it ideal for bioinformatics, computational biology, and other graph-based applications.

r-bayesmix 0.7-6
Propagated dependencies: r-rjags@4-17 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://statmath.wu.ac.at/~gruen/BayesMix/
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Bayesian Mixture Models with JAGS
Description:

Fits finite mixture models of univariate Gaussian distributions using JAGS within a Bayesian framework.

r-betanb 1.0.6
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/jeksterslab/betaNB
Licenses: Expat
Build system: r
Synopsis: Bootstrap for Regression Effect Sizes
Description:

Generates nonparametric bootstrap confidence intervals (Efron and Tibshirani, 1993: <doi:10.1201/9780429246593>) for standardized regression coefficients (beta) and other effect sizes, including multiple correlation, semipartial correlations, improvement in R-squared, squared partial correlations, and differences in standardized regression coefficients, for models fitted by lm().

r-braggr 0.1.1
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=braggR
Licenses: GPL 2
Build system: r
Synopsis: Calculate the Revealed Aggregator of Probability Predictions
Description:

Forecasters predicting the chances of a future event may disagree due to differing evidence or noise. To harness the collective evidence of the crowd, Ville Satopää (2021) "Regularized Aggregation of One-off Probability Predictions" <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3769945> proposes a Bayesian aggregator that is regularized by analyzing the forecasters disagreement and ascribing over-dispersion to noise. This aggregator requires no user intervention and can be computed efficiently even for a large numbers of predictions. The author evaluates the aggregator on subjective probability predictions collected during a four-year forecasting tournament sponsored by the US intelligence community. The aggregator improves the accuracy of simple averaging by around 20% and other state-of-the-art aggregators by 10-25%. The advantage stems almost exclusively from improved calibration. This aggregator -- know as "the revealed aggregator" -- inputs a) forecasters probability predictions (p) of a future binary event and b) the forecasters common prior (p0) of the future event. In this R-package, the function sample_aggregator(p,p0,...) allows the user to calculate the revealed aggregator. Its use is illustrated with a simple example.

r-bssprep 0.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BSSprep
Licenses: GPL 2+
Build system: r
Synopsis: Whitening Data as Preparation for Blind Source Separation
Description:

Whitening is the first step of almost all blind source separation (BSS) methods. A fast implementation of whitening for BSS is implemented to serve as a lightweight dependency for packages providing BSS methods.

r-blvim 0.1.1
Propagated dependencies: r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-collapse@2.1.5 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=blvim
Licenses: GPL 3+
Build system: r
Synopsis: Boltzmann–Lotka–Volterra Interaction Model
Description:

Estimates Boltzmannâ Lotkaâ Volterra (BLV) interaction model efficiently. Enables programmatic and graphical exploration of the solution space of BLV models when parameters are varied. See Wilson, A. (2008) <dx.doi.org/10.1098/rsif.2007.1288>.

r-blindreview 2.0.0
Dependencies: gmp@6.3.0
Propagated dependencies: r-hmisc@5.2-4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=blindreview
Licenses: GPL 3+
Build system: r
Synopsis: Enables Blind Review of Database
Description:

Randomly reassigns the group identifications to one of the variables of the database, say Treatment, and randomly reassigns the observation numbers of the dataset. Reorders the observations according to these new numbers. Centers each group of Treatment at the grand mean in order to further mask the treatment. An unmasking function is provided so that the user can identify the potential outliers in terms of their original values when blinding is no longer needed. It is suggested that a forward search procedure be performed on the masked data. Details of some forward search functions may be found in <https://CRAN.R-project.org/package=forsearch>.

r-blakerci 1.0-6
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BlakerCI
Licenses: GPL 3
Build system: r
Synopsis: Blaker's Binomial and Poisson Confidence Limits
Description:

Fast and accurate calculation of Blaker's binomial and Poisson confidence limits (and some related stuff).

r-bigplscox 0.8.1
Propagated dependencies: r-survival@3.8-3 r-survcomp@1.60.0 r-survauc@1.4-0 r-sgpls@1.8.1 r-rms@8.1-0 r-risksetroc@1.0.4.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-kernlab@0.9-33 r-foreach@1.5.2 r-doparallel@1.0.17 r-caret@7.0-1 r-bigsurvsgd@0.0.1 r-bigmemory@4.6.4 r-bigalgebra@3.0.0 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://fbertran.github.io/bigPLScox/
Licenses: GPL 3
Build system: r
Synopsis: Partial Least Squares for Cox Models with Big Matrices
Description:

This package provides Partial least squares Regression and various regular, sparse or kernel, techniques for fitting Cox models for big data. Provides a Partial Least Squares (PLS) algorithm adapted to Cox proportional hazards models that works with bigmemory matrices without loading the entire dataset in memory. Also implements a gradient-descent based solver for Cox proportional hazards models that works directly on bigmemory matrices. Bertrand and Maumy (2023) <https://hal.science/hal-05352069>, and <https://hal.science/hal-05352061> highlighted fitting and cross-validating PLS-based Cox models to censored big data.

r-bivarian 1.0.3
Propagated dependencies: r-tidyr@1.3.1 r-table1@1.5.1 r-systemfonts@1.3.1 r-scales@1.4.0 r-rrtable@0.3.0 r-rlang@1.1.6 r-magrittr@2.0.4 r-logistf@1.26.1 r-lifecycle@1.0.4 r-glue@1.8.0 r-ggprism@1.0.7 r-ggplot2@4.0.1 r-fastdummies@1.7.5 r-epitools@0.5-10.1 r-dplyr@1.1.4 r-desctools@0.99.60 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/AndresFloresG/BiVariAn
Licenses: GPL 3+
Build system: r
Synopsis: Bivariate Automatic Analysis
Description:

Simplify bivariate and regression analyses by automating result generation, including summary tables, statistical tests, and customizable graphs. It supports tests for continuous and dichotomous data, as well as stepwise regression for linear, logistic, and Firth penalized logistic models. While not a substitute for tailored analysis, BiVariAn accelerates workflows and is expanding features like multilingual interpretations of results.The methods for selecting significant statistical tests, as well as the predictor selection in prediction functions, can be referenced in the works of Marc Kery (2003) <doi:10.1890/0012-9623(2003)84[92:NORDIG]2.0.CO;2> and Rainer Puhr (2017) <doi:10.1002/sim.7273>.

r-bayesvl 1.0.0
Propagated dependencies: r-viridis@0.6.5 r-stanheaders@2.32.10 r-rstan@2.32.7 r-reshape2@1.4.5 r-ggplot2@4.0.1 r-coda@0.19-4.1 r-bnlearn@5.1 r-bayesplot@1.14.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/sshpa/bayesvl
Licenses: GPL 3+
Build system: r
Synopsis: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with 'Stan'
Description:

This package provides users with its associated functions for pedagogical purposes in visually learning Bayesian networks and Markov chain Monte Carlo (MCMC) computations. It enables users to: a) Create and examine the (starting) graphical structure of Bayesian networks; b) Create random Bayesian networks using a dataset with customized constraints; c) Generate Stan code for structures of Bayesian networks for sampling the data and learning parameters; d) Plot the network graphs; e) Perform Markov chain Monte Carlo computations and produce graphs for posteriors checks. The package refers to one reference item, which describes the methods and algorithms: Vuong, Quan-Hoang and La, Viet-Phuong (2019) <doi:10.31219/osf.io/w5dx6> The bayesvl R package. Open Science Framework (May 18).

r-binancer 1.2.0
Propagated dependencies: r-snakecase@0.11.1 r-logger@0.4.1 r-jsonlite@2.0.0 r-httr@1.4.7 r-digest@0.6.39 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://daroczig.github.io/binancer/
Licenses: FSDG-compatible
Build system: r
Synopsis: API Client to 'Binance'
Description:

R client to the Binance Public Rest API for data collection on cryptocurrencies, portfolio management and trading: <https://github.com/binance/binance-spot-api-docs/blob/master/rest-api.md>.

r-biplotez 2.2
Propagated dependencies: r-withr@3.0.2 r-plotrix@3.8-13
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=biplotEZ
Licenses: Expat
Build system: r
Synopsis: EZ-to-Use Biplots
Description:

This package provides users with an EZ-to-use platform for representing data with biplots. Currently principal component analysis (PCA), canonical variate analysis (CVA) and simple correspondence analysis (CA) biplots are included. This is accompanied by various formatting options for the samples and axes. Alpha-bags and concentration ellipses are included for visual enhancements and interpretation. For an extensive discussion on the topic, see Gower, J.C., Lubbe, S. and le Roux, N.J. (2011, ISBN: 978-0-470-01255-0) Understanding Biplots. Wiley: Chichester.

r-bhh2 2016.05.31
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BHH2
Licenses: GPL 2+
Build system: r
Synopsis: Useful Functions for Box, Hunter and Hunter II
Description:

This package provides functions and data sets reproducing some examples in Box, Hunter and Hunter II. Useful for statistical design of experiments, especially factorial experiments.

r-bttest 0.10.3
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/Paul-Haimerl/BTtest
Licenses: GPL 3+
Build system: r
Synopsis: Estimate the Number of Factors in Large Nonstationary Datasets
Description:

Large panel data sets are often subject to common trends. However, it can be difficult to determine the exact number of these common factors and analyse their properties. The package implements the Barigozzi and Trapani (2022) <doi:10.1080/07350015.2021.1901719> test, which not only provides an efficient way of estimating the number of common factors in large nonstationary panel data sets, but also gives further insights on factor classes. The routine identifies the existence of (i) a factor subject to a linear trend, (ii) the number of zero-mean I(1) and (iii) zero-mean I(0) factors. Furthermore, the package includes the Integrated Panel Criteria by Bai (2004) <doi:10.1016/j.jeconom.2003.10.022> that provide a complementary measure for the number of factors.

r-bigpcacpp 0.9.0
Propagated dependencies: r-withr@3.0.2 r-rcpp@1.1.0 r-bigmemory@4.6.4 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://fbertran.github.io/bigPCAcpp/
Licenses: GPL 2+
Build system: r
Synopsis: Principal Component Analysis for 'bigmemory' Matrices
Description:

High performance principal component analysis routines that operate directly on bigmemory::big.matrix objects. The package avoids materialising large matrices in memory by streaming data through BLAS and LAPACK kernels and provides helpers to derive scores, loadings, correlations, and contribution diagnostics, including utilities that stream results into bigmemory'-backed matrices for file-based workflows. Additional interfaces expose scalable singular value decomposition, robust PCA, and robust SVD algorithms so that users can explore large matrices while tempering the influence of outliers. Scalable principal component analysis is also implemented, Elgamal, Yabandeh, Aboulnaga, Mustafa, and Hefeeda (2015) <doi:10.1145/2723372.2751520>.

r-batchexperiments 1.4.4
Propagated dependencies: r-rsqlite@2.4.4 r-dbi@1.2.3 r-data-table@1.17.8 r-checkmate@2.3.3 r-bbmisc@1.13 r-batchjobs@1.10 r-backports@1.5.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/tudo-r/BatchExperiments
Licenses: Modified BSD
Build system: r
Synopsis: Statistical Experiments on Batch Computing Clusters
Description:

Extends the BatchJobs package to run statistical experiments on batch computing clusters. For further details see the project web page.

r-browndog 0.2.1
Propagated dependencies: r-rcurl@1.98-1.17 r-jsonlite@2.0.0 r-httpuv@1.6.16
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BrownDog
Licenses: FSDG-compatible FSDG-compatible
Build system: r
Synopsis: Brown Dog R Interface
Description:

An R interface for the Brown Dog which allows researchers to leverage Brown Dog Services that provides modules to identify the conversion options for a file, to convert file to appropriate format, or to extract data from a file. See <http://browndog.ncsa.illinois.edu/> for more information.

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Total results: 68658