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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-blmengineinr 0.1.7
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-openxlsx@4.2.8.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://www.windwardenv.com/biotic-ligand-model/
Licenses: FSDG-compatible
Build system: r
Synopsis: Biotic Ligand Model Engine
Description:

This package provides a chemical speciation and toxicity prediction model for the toxicity of metals to aquatic organisms. The Biotic Ligand Model (BLM) engine was originally programmed in PowerBasic by Robert Santore and others. The main way the BLM can be used is to predict the toxicity of a metal to an organism with a known sensitivity (i.e., it is known how much of that metal must accumulate on that organism's biotic ligand to cause a physiological effect in a certain percentage of the population, such as a 20% loss in reproduction or a 50% mortality rate). The second way the BLM can be used is to estimate the chemical speciation of the metal and other constituents in water, including estimating the amount of metal accumulated to an organism's biotic ligand during a toxicity test. In the first application of the BLM, the amount of metal associated with a toxicity endpoint, or regulatory limit will be predicted, while in the second application, the amount of metal is known and the portions of that metal that exist in various forms will be determined. This version of the engine has been re-structured to perform the calculations in a different way that will make it more efficient in R, while also making it more flexible and easier to maintain in the future. Because of this, it does not currently match the desktop model exactly, but we hope to improve this comparability in the future.

r-bayestreeprior 1.0.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BayesTreePrior
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Tree Prior Simulation
Description:

This package provides a way to simulate from the prior distribution of Bayesian trees by Chipman et al. (1998) <DOI:10.2307/2669832>. The prior distribution of Bayesian trees is highly dependent on the design matrix X, therefore using the suggested hyperparameters by Chipman et al. (1998) <DOI:10.2307/2669832> is not recommended and could lead to unexpected prior distribution. This work is part of my master thesis (expected 2016).

r-bernadette 1.1.6
Propagated dependencies: r-stanheaders@2.32.10 r-scales@1.4.0 r-rstantools@2.5.0 r-rstan@2.32.7 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-magrittr@2.0.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://bernadette-eu.github.io/
Licenses: GPL 3+
Build system: r
Synopsis: Bayesian Inference and Model Selection for Stochastic Epidemics
Description:

Bayesian analysis for stochastic extensions of non-linear dynamic systems using advanced computational algorithms. Described in Bouranis, L., Demiris, N., Kalogeropoulos, K., and Ntzoufras, I. (2022) <doi:10.48550/arXiv.2211.15229>.

r-bartcause 1.0-10
Propagated dependencies: r-dbarts@0.9-32
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/vdorie/bartCause
Licenses: GPL 2+
Build system: r
Synopsis: Causal Inference using Bayesian Additive Regression Trees
Description:

This package contains a variety of methods to generate typical causal inference estimates using Bayesian Additive Regression Trees (BART) as the underlying regression model (Hill (2012) <doi:10.1198/jcgs.2010.08162>).

r-belg 1.5.3
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://r-spatialecology.github.io/belg/
Licenses: Expat
Build system: r
Synopsis: Boltzmann Entropy of a Landscape Gradient
Description:

Calculates the Boltzmann entropy of a landscape gradient. This package uses the analytical method created by Gao, P., Zhang, H. and Li, Z., 2018 (<doi:10.1111/tgis.12315>) and by Gao, P. and Li, Z., 2019 (<doi:10.1007/s10980-019-00854-3>). It also extend the original ideas by allowing calculations on data with missing values.

r-bayesnec 2.1.3.1
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-loo@2.8.0 r-ggplot2@4.0.1 r-formula-tools@1.7.1 r-evaluate@1.0.5 r-dplyr@1.1.4 r-chk@0.10.0 r-brms@2.23.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://open-aims.github.io/bayesnec/
Licenses: GPL 2
Build system: r
Synopsis: Bayesian No-Effect- Concentration (NEC) Algorithm
Description:

Implementation of No-Effect-Concentration estimation that uses brms (see Burkner (2017)<doi:10.18637/jss.v080.i01>; Burkner (2018)<doi:10.32614/RJ-2018-017>; Carpenter et al. (2017)<doi:10.18637/jss.v076.i01> to fit concentration(dose)-response data using Bayesian methods for the purpose of estimating ECx values, but more particularly NEC (see Fox (2010)<doi:10.1016/j.ecoenv.2009.09.012>), NSEC (see Fisher and Fox (2023)<doi:10.1002/etc.5610>), and N(S)EC (see Fisher et al. 2023<doi:10.1002/ieam.4809>). A full description of this package can be found in Fisher et al. (2024)<doi:10.18637/jss.v110.i05>. This package expands and supersedes an original version implemented in R2jags (see Su and Yajima (2020)<https://CRAN.R-project.org/package=R2jags>; Fisher et al. (2020)<doi:10.5281/ZENODO.3966864>).

r-bootstraptests 0.1.0
Propagated dependencies: r-pbapply@1.7-4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/AlexisDerumigny/BootstrapTests
Licenses: GPL 3
Build system: r
Synopsis: Bootstrap-Based Hypothesis Testing using Different Resampling Schemes
Description:

Perform bootstrap-based hypothesis testing procedures on three statistical problems. In particular, it covers independence testing, testing the slope in a linear regression setting, and goodness-of-fit testing, following (Derumigny, Galanis, Schipper and Van der Vaart, 2025) <doi:10.48550/arXiv.2512.10546>.

r-bpca 1.3-8
Propagated dependencies: r-xtable@1.8-4 r-scatterplot3d@0.3-44 r-rgl@1.3.31
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/jcfaria/bpca
Licenses: GPL 2+
Build system: r
Synopsis: Biplot of Multivariate Data Based on Principal Components Analysis
Description:

This package implements biplot (2d and 3d) of multivariate data based on principal components analysis and diagnostic tools of the quality of the reduction.

r-buoyant 0.1.0
Propagated dependencies: r-yaml@2.3.10 r-withr@3.0.2 r-ssh@0.9.4 r-renv@1.1.5 r-jsonlite@2.0.0 r-analogsea@1.0.7.2
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://posit-dev.github.io/buoyant/
Licenses: Expat
Build system: r
Synopsis: Deploy '_server.yml' Compliant Applications to 'DigitalOcean'
Description:

This package provides tools to deploy R web server applications that follow the _server.yml standard. This standard allows different R server frameworks ('plumber2', fiery', etc.) to be deployed using a common interface. The package supports deployment to DigitalOcean and includes validation tools to ensure _server.yml files are correctly formatted.

r-bsvars 3.2
Propagated dependencies: r-stochvol@3.2.9 r-rcpptn@0.2-2 r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-r6@2.6.1 r-gigrvg@0.8
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://bsvars.org/bsvars/
Licenses: GPL 3+
Build system: r
Synopsis: Bayesian Estimation of Structural Vector Autoregressive Models
Description:

This package provides fast and efficient procedures for Bayesian analysis of Structural Vector Autoregressions. This package estimates a wide range of models, including homo-, heteroskedastic, and non-normal specifications. Structural models can be identified by adjustable exclusion restrictions, time-varying volatility, or non-normality. They all include a flexible three-level equation-specific local-global hierarchical prior distribution for the estimated level of shrinkage for autoregressive and structural parameters. Additionally, the package facilitates predictive and structural analyses such as impulse responses, forecast error variance and historical decompositions, forecasting, verification of heteroskedasticity, non-normality, and hypotheses on autoregressive parameters, as well as analyses of structural shocks, volatilities, and fitted values. Beautiful plots, informative summary functions, and extensive documentation including the vignette by Woźniak (2024) <doi:10.48550/arXiv.2410.15090> complement all this. The implemented techniques align closely with those presented in Lütkepohl, Shang, Uzeda, & Woźniak (2024) <doi:10.48550/arXiv.2404.11057>, Lütkepohl & Woźniak (2020) <doi:10.1016/j.jedc.2020.103862>, and Song & Woźniak (2021) <doi:10.1093/acrefore/9780190625979.013.174>. The bsvars package is aligned regarding objects, workflows, and code structure with the R package bsvarSIGNs by Wang & Woźniak (2024) <doi:10.32614/CRAN.package.bsvarSIGNs>, and they constitute an integrated toolset.

r-biostats 1.1.2
Propagated dependencies: r-rlang@1.1.6 r-nortest@1.0-4 r-gt@1.3.0 r-gridextra@2.3 r-ggplot2@4.0.1 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/sebasquirarte/biostats
Licenses: Expat
Build system: r
Synopsis: Biostatistics and Clinical Data Analysis
Description:

Biostatistical and clinical data analysis, including descriptive statistics, exploratory data analysis, sample size and power calculations, statistical inference, and data visualization. Normality tests are implemented following Mishra et al. (2019) <doi:10.4103/aca.ACA_157_18>, omnibus test procedures are based on Blanca et al. (2017) <doi:10.3758/s13428-017-0918-2> and Field et al. (2012, ISBN:9781446200469), while sample size and power calculation methods follow Chow et al. (2017) <doi:10.1201/9781315183084>.

r-binomci 1.3
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=binomCI
Licenses: GPL 2+
Build system: r
Synopsis: Confidence Intervals for a Binomial Proportion
Description:

Twelve confidence intervals for one binomial proportion or a vector of binomial proportions are computed. The confidence intervals are: Jeffreys, Wald, Wald corrected, Wald, Blyth and Still, Agresti and Coull, Wilson, Score, Score corrected, Wald logit, Wald logit corrected, Arcsine and Exact binomial. References include, among others: Vollset, S. E. (1993). "Confidence intervals for a binomial proportion". Statistics in Medicine, 12(9): 809-824. <doi:10.1002/sim.4780120902>.

r-btdecaylasso 0.1.1
Propagated dependencies: r-optimx@2025-4.9 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BTdecayLasso
Licenses: GPL 2+
Build system: r
Synopsis: Bradley-Terry Model with Exponential Time Decayed Log-Likelihood and Adaptive Lasso
Description:

We utilize the Bradley-Terry Model to estimate the abilities of teams using paired comparison data. For dynamic approximation of current rankings, we employ the Exponential Decayed Log-likelihood function, and we also apply the Lasso penalty for variance reduction and grouping. The main algorithm applies the Augmented Lagrangian Method described by Masarotto and Varin (2012) <doi:10.1214/12-AOAS581>.

r-basinet 0.0.5
Propagated dependencies: r-rweka@0.4-47 r-rmcfs@1.3.6 r-rjava@1.0-11 r-randomforest@4.7-1.2 r-igraph@2.2.1 r-biostrings@2.78.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BASiNET
Licenses: GPL 3
Build system: r
Synopsis: Classification of RNA Sequences using Complex Network Theory
Description:

It makes the creation of networks from sequences of RNA, with this is done the abstraction of characteristics of these networks with a methodology of threshold for the purpose of making a classification between the classes of the sequences. There are four data present in the BASiNET package, "sequences", "sequences2", "sequences-predict" and "sequences2-predict" with 11, 10, 11 and 11 sequences respectively. These sequences were taken from the data set used in the article (LI, Aimin; ZHANG, Junying; ZHOU, Zhongyin, 2014) <doi:10.1186/1471-2105-15-311>, these sequences are used to run examples. The BASiNET was published on Nucleic Acids Research, (ITO, Eric; KATAHIRA, Isaque; VICENTE, Fábio; PEREIRA, Felipe; LOPES, Fabrà cio, 2018) <doi:10.1093/nar/gky462>.

r-busdater 0.2.0
Propagated dependencies: r-lubridate@1.9.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://mickmioduszewski.github.io/busdater/
Licenses: Expat
Build system: r
Synopsis: Standard Date Calculations for Business
Description:

Get a current financial year, start of current month, End of current month, start of financial year and end of it. Allow for offset from the date.

r-blockcv 3.2-0
Propagated dependencies: r-terra@1.8-86 r-sp@2.2-0 r-sf@1.0-23 r-rcpp@1.1.0 r-ggplot2@4.0.1 r-cowplot@1.2.0 r-automap@1.1-20
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/rvalavi/blockCV
Licenses: GPL 3+
Build system: r
Synopsis: Spatial and Environmental Blocking for K-Fold and LOO Cross-Validation
Description:

Creating spatially or environmentally separated folds for cross-validation to provide a robust error estimation in spatially structured environments; Investigating and visualising the effective range of spatial autocorrelation in continuous raster covariates and point samples to find an initial realistic distance band to separate training and testing datasets spatially described in Valavi, R. et al. (2019) <doi:10.1111/2041-210X.13107>.

r-biotic 0.1.2
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/robbriers/biotic
Licenses: GPL 3
Build system: r
Synopsis: Calculation of Freshwater Biotic Indices
Description:

Calculates a range of UK freshwater invertebrate biotic indices including BMWP, Whalley, WHPT, Habitat-specific BMWP, AWIC, LIFE and PSI.

r-bayesgof 5.2
Propagated dependencies: r-vgam@1.1-13 r-orthopolynom@1.0-6.1 r-nleqslv@3.3.5 r-bolstad2@1.0-29
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BayesGOF
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Modeling via Frequentist Goodness-of-Fit
Description:

This package provides a Bayesian data modeling scheme that performs four interconnected tasks: (i) characterizes the uncertainty of the elicited parametric prior; (ii) provides exploratory diagnostic for checking prior-data conflict; (iii) computes the final statistical prior density estimate; and (iv) executes macro- and micro-inference. Primary reference is Mukhopadhyay, S. and Fletcher, D. 2018 paper "Generalized Empirical Bayes via Frequentist Goodness of Fit" (<https://www.nature.com/articles/s41598-018-28130-5 >).

r-blrpm 1.0
Propagated dependencies: r-r6@2.6.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BLRPM
Licenses: GPL 2+
Build system: r
Synopsis: Stochastic Rainfall Generator Bartlett-Lewis Rectangular Pulse Model
Description:

Due to a limited availability of observed high-resolution precipitation records with adequate length, simulations with stochastic precipitation models are used to generate series for subsequent studies [e.g. Khaliq and Cunmae, 1996, <doi:10.1016/0022-1694(95)02894-3>, Vandenberghe et al., 2011, <doi:10.1029/2009WR008388>]. This package contains an R implementation of the original Bartlett-Lewis rectangular pulse model (BLRPM), developed by Rodriguez-Iturbe et al. (1987) <doi:10.1098/rspa.1987.0039>. It contains a function for simulating a precipitation time series based on storms and cells generated by the model with given or estimated model parameters. Additionally BLRPM parameters can be estimated from a given or simulated precipitation time series. The model simulations can be plotted in a three-layer plot including an overview of generated storms and cells by the model (which can also be plotted individually), a continuous step-function and a discrete precipitation time series at a chosen aggregation level.

r-biogrowth 1.0.8
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-mvtnorm@1.3-3 r-mass@7.3-65 r-lifecycle@1.0.4 r-lamw@2.2.5 r-ggplot2@4.0.1 r-formula-tools@1.7.1 r-fme@1.3.6.4 r-dplyr@1.1.4 r-desolve@1.40 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=biogrowth
Licenses: GPL 3
Build system: r
Synopsis: Modelling of Population Growth
Description:

Modelling of population growth under static and dynamic environmental conditions. Includes functions for model fitting and making prediction under isothermal and dynamic conditions. The methods (algorithms & models) are based on predictive microbiology (See Perez-Rodriguez and Valero (2012, ISBN:978-1-4614-5519-6)).

r-blockmatrix 1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: http://cri.gmpf.eu/Research/Sustainable-Agro-Ecosystems-and-Bioresources/Dynamics-in-the-agro-ecosystems/people/Emanuele-Cordano
Licenses: GPL 2+
Build system: r
Synopsis: blockmatrix: Tools to solve algebraic systems with partitioned matrices
Description:

Some elementary matrix algebra tools are implemented to manage block matrices or partitioned matrix, i.e. "matrix of matrices" (http://en.wikipedia.org/wiki/Block_matrix). The block matrix is here defined as a new S3 object. In this package, some methods for "matrix" object are rewritten for "blockmatrix" object. New methods are implemented. This package was created to solve equation systems with block matrices for the analysis of environmental vector time series . Bugs/comments/questions/collaboration of any kind are warmly welcomed.

r-biomontools 1.2.4
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-rlang@1.1.6 r-maps@3.4.3 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/leppott/BioMonTools
Licenses: Expat
Build system: r
Synopsis: Biomonitoring and Bioassessment Calculations
Description:

An aid for manipulating data associated with biomonitoring and bioassessment. Calculations include metric calculation, marking of excluded taxa, subsampling, and multimetric index calculation. Targeted communities are benthic macroinvertebrates, fish, periphyton, and coral. As described in the Revised Rapid Bioassessment Protocols (Barbour et al. 1999) <https://archive.epa.gov/water/archive/web/html/index-14.html>.

r-biodem 0.5
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=Biodem
Licenses: GPL 2
Build system: r
Synopsis: Biodemography Functions
Description:

The Biodem package provides a number of functions for Biodemographic analysis.

r-bingat 1.3
Propagated dependencies: r-vegan@2.7-2 r-network@1.19.0 r-matrixstats@1.5.0 r-gplots@3.2.0 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bingat
Licenses: ASL 2.0
Build system: r
Synopsis: Binary Graph Analysis Tools
Description:

This package provides tools to analyze binary graph objects.

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Total results: 69112