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      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
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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-automagic 0.5.1
Propagated dependencies: r-yaml@2.3.10 r-remotes@2.5.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-knitr@1.50 r-formatr@1.14 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/cole-brokamp/automagic
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Automagically Document and Install Packages Necessary to Run R Code
Description:

Parse R code in a given directory for R packages and attempt to install them from CRAN or GitHub. Optionally use a dependencies file for tighter control over which package versions to install.

r-ascotracer 0.0.1
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-purrr@1.2.0 r-lutz@0.3.2 r-lubridate@1.9.4 r-data-table@1.17.8 r-circular@0.5-2
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/IhsanKhaliq/ascotraceR
Licenses: Expat
Build system: r
Synopsis: Simulate the Spread of Ascochyta Blight in Chickpea
Description:

This package provides a spatiotemporal model that simulates the spread of Ascochyta blight in chickpea fields based on location-specific weather conditions. This model is adapted from a model developed by Diggle et al. (2002) <doi:10.1094/PHYTO.2002.92.10.1110> for simulating the spread of anthracnose in a lupin field.

r-aldqr 1.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=ALDqr
Licenses: GPL 3+
Build system: r
Synopsis: Quantile Regression Using Asymmetric Laplace Distribution
Description:

EM algorithm for estimation of parameters and other methods in a quantile regression.

r-addhazard 1.1.0
Propagated dependencies: r-survival@3.8-3 r-rootsolve@1.8.2.4 r-ahaz@1.15.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=addhazard
Licenses: GPL 2
Build system: r
Synopsis: Fit Additive Hazards Models for Survival Analysis
Description:

This package contains tools to fit the additive hazards model to data from a cohort, random sampling, two-phase Bernoulli sampling and two-phase finite population sampling, as well as calibration tool to incorporate phase I auxiliary information into the two-phase data model fitting. This package provides regression parameter estimates and their model-based and robust standard errors. It also offers tools to make prediction of individual specific hazards.

r-adlp 0.1.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/agi-lab/ADLP
Licenses: GPL 3
Build system: r
Synopsis: Accident and Development Period Adjusted Linear Pools for Actuarial Stochastic Reserving
Description:

Loss reserving generally focuses on identifying a single model that can generate superior predictive performance. However, different loss reserving models specialise in capturing different aspects of loss data. This is recognised in practice in the sense that results from different models are often considered, and sometimes combined. For instance, actuaries may take a weighted average of the prediction outcomes from various loss reserving models, often based on subjective assessments. This package allows for the use of a systematic framework to objectively combine (i.e. ensemble) multiple stochastic loss reserving models such that the strengths offered by different models can be utilised effectively. Our framework is developed in Avanzi et al. (2023). Firstly, our criteria model combination considers the full distributional properties of the ensemble and not just the central estimate - which is of particular importance in the reserving context. Secondly, our framework is that it is tailored for the features inherent to reserving data. These include, for instance, accident, development, calendar, and claim maturity effects. Crucially, the relative importance and scarcity of data across accident periods renders the problem distinct from the traditional ensemble techniques in statistical learning. Our framework is illustrated with a complex synthetic dataset. In the results, the optimised ensemble outperforms both (i) traditional model selection strategies, and (ii) an equally weighted ensemble. In particular, the improvement occurs not only with central estimates but also relevant quantiles, such as the 75th percentile of reserves (typically of interest to both insurers and regulators). Reference: Avanzi B, Li Y, Wong B, Xian A (2023) "Ensemble distributional forecasting for insurance loss reserving" <doi:10.48550/arXiv.2206.08541>.

r-abclass 0.5.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://wwenjie.org/abclass
Licenses: GPL 3+
Build system: r
Synopsis: Angle-Based Classification
Description:

Multi-category angle-based large-margin classifiers. See Zhang and Liu (2014) <doi:10.1093/biomet/asu017> for details.

r-assist 3.1.9
Propagated dependencies: r-nlme@3.1-168 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://yuedong.faculty.pstat.ucsb.edu/software.html
Licenses: GPL 2
Build system: r
Synopsis: Suite of R Functions Implementing Spline Smoothing Techniques
Description:

Fit various smoothing spline models. Includes an ssr() function for smoothing spline regression, an nnr() function for nonparametric nonlinear regression, an snr() function for semiparametric nonlinear regression, an slm() function for semiparametric linear mixed-effects models, and an snm() function for semiparametric nonlinear mixed-effects models. See Wang (2011) <doi:10.1201/b10954> for an overview.

r-airship 1.4.3
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=airship
Licenses: GPL 3
Build system: r
Synopsis: Visualization of Simulated Datasets with Multiple Simulation Input Dimensions
Description:

Plots simulation results of clinical trials. Its main feature is allowing users to simultaneously investigate the impact of several simulation input dimensions through dynamic filtering of the simulation results. A more detailed description of the app can be found in Meyer et al. <DOI:10.1016/j.softx.2023.101347> or the vignettes on GitHub'.

r-amr 3.0.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://amr-for-r.org
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: Antimicrobial Resistance Data Analysis
Description:

This package provides functions to simplify and standardise antimicrobial resistance (AMR) data analysis and to work with microbial and antimicrobial properties by using evidence-based methods, as described in <doi:10.18637/jss.v104.i03>.

r-akima 0.6-3.6
Propagated dependencies: r-sp@2.2-0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=akima
Licenses: FSDG-compatible
Build system: r
Synopsis: Interpolation of Irregularly and Regularly Spaced Data
Description:

Several cubic spline interpolation methods of H. Akima for irregular and regular gridded data are available through this package, both for the bivariate case (irregular data: ACM 761, regular data: ACM 760) and univariate case (ACM 433 and ACM 697). Linear interpolation of irregular gridded data is also covered by reusing D. J. Renkas triangulation code which is part of Akimas Fortran code. A bilinear interpolator for regular grids was also added for comparison with the bicubic interpolator on regular grids. Please note that most of the functions are now also covered in package interp, which is a re-implementation from scratch under a free license.

r-addhaz 0.5
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=addhaz
Licenses: GPL 3
Build system: r
Synopsis: Binomial and Multinomial Additive Hazard Models
Description:

This package provides functions to fit the binomial and multinomial additive hazard models and to estimate the contribution of diseases/conditions to the disability prevalence, as proposed by Nusselder and Looman (2004) and extended by Yokota et al (2017).

r-ardec 2.1-1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=ArDec
Licenses: GPL 2+
Build system: r
Synopsis: Time Series Autoregressive-Based Decomposition
Description:

Autoregressive-based decomposition of a time series based on the approach in West (1997). Particular cases include the extraction of trend and seasonal components.

r-autotransqf 0.1.3
Propagated dependencies: r-vgam@1.1-13 r-moments@0.14.1 r-matlab2r@1.5.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/yyyuehhu/AutoTransQF
Licenses: GPL 3
Build system: r
Synopsis: Novel Automatic Shifted Log Transformation
Description:

This package provides a novel parametrization of log transformation and a shift parameter to automate the transformation process are proposed in R package AutoTransQF based on Feng et al. (2016). Please read Feng et al. (2016) <doi:10.1002/sta4.104> for more details of the method.

r-amvenndiagram5 1.0.0
Propagated dependencies: r-venn@1.12 r-partitions@1.10-9 r-htmlwidgets@1.6.4
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/stla/amVennDiagram5
Licenses: GPL 3
Build system: r
Synopsis: Interactive Venn Diagrams
Description:

This package creates interactive Venn diagrams using the amCharts5 library for JavaScript'. They can be used directly from the R console, from RStudio', in shiny applications, and in rmarkdown documents.

r-aoristic 1.1.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=aoristic
Licenses: GPL 3
Build system: r
Synopsis: Generates Aoristic Probability Distributions
Description:

It can sometimes be difficult to ascertain when some events (such as property crime) occur because the victim is not present when the crime happens. As a result, police databases often record a start (or from') date and time, and an end (or to') date and time. The time span between these date/times can be minutes, hours, or sometimes days, hence the term Aoristic'. Aoristic is one of the past tenses in Greek and represents an uncertain occurrence in time. For events with a location describes with either a latitude/longitude, or X,Y coordinate pair, and a start and end date/time, this package generates an aoristic data frame with aoristic weighted probability values for each hour of the week, for each observation. The coordinates are not necessary for the program to calculate aoristic weights; however, they are part of this package because a spatial component has been integral to aoristic analysis from the start. Dummy coordinates can be introduced if the user only has temporal data. Outputs include an aoristic data frame, as well as summary graphs and displays. For more information see: Ratcliffe, JH (2002) Aoristic signatures and the temporal analysis of high volume crime patterns, Journal of Quantitative Criminology. 18 (1): 23-43. Note: This package replaces an original aoristic package (version 0.6) by George Kikuchi that has been discontinued with his permission.

r-alfq 1.3.6
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/aLFQ
Licenses: GPL 3+
Build system: r
Synopsis: Estimating Absolute Protein Quantities from Label-Free LC-MS/MS Proteomics Data
Description:

Determination of absolute protein quantities is necessary for multiple applications, such as mechanistic modeling of biological systems. Quantitative liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics can measure relative protein abundance on a system-wide scale. To estimate absolute quantitative information using these relative abundance measurements requires additional information such as heavy-labeled references of known concentration. Multiple methods have been using different references and strategies; some are easily available whereas others require more effort on the users end. Hence, we believe the field might benefit from making some of these methods available under an automated framework, which also facilitates validation of the chosen strategy. We have implemented the most commonly used absolute label-free protein abundance estimation methods for LC-MS/MS modes quantifying on either MS1-, MS2-levels or spectral counts together with validation algorithms to enable automated data analysis and error estimation. Specifically, we used Monte-carlo cross-validation and bootstrapping for model selection and imputation of proteome-wide absolute protein quantity estimation. Our open-source software is written in the statistical programming language R and validated and demonstrated on a synthetic sample.

r-aramappings 0.1.3
Propagated dependencies: r-slam@0.1-55 r-rglpk@0.6-5.1 r-pracma@2.4.6 r-matrix@1.7-4 r-glpkapi@1.3.4.1 r-ggplot2@4.0.1 r-cvxr@1.0-15 r-clarabel@0.11.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/manuelrubio/aramappings
Licenses: Expat
Build system: r
Synopsis: Computes Adaptable Radial Axes Mappings
Description:

Computes low-dimensional point representations of high-dimensional numerical data according to the data visualization method Adaptable Radial Axes described in: Manuel Rubio-Sánchez, Alberto Sanchez, and Dirk J. Lehmann (2017) "Adaptable radial axes plots for improved multivariate data visualization" <doi:10.1111/cgf.13196>.

r-archaeophases 2.1.0
Propagated dependencies: r-arkhe@1.11.0 r-aion@1.7.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://ArchaeoStat.github.io/ArchaeoPhases/
Licenses: GPL 3+
Build system: r
Synopsis: Post-Processing of Markov Chain Monte Carlo Simulations for Chronological Modelling
Description:

Statistical analysis of archaeological dates and groups of dates. This package allows to post-process Markov Chain Monte Carlo (MCMC) simulations from ChronoModel <https://chronomodel.com/>, Oxcal <https://c14.arch.ox.ac.uk/oxcal.html> or BCal <https://bcal.shef.ac.uk/>. It provides functions for the study of rhythms of the long term from the posterior distribution of a series of dates (tempo and activity plot). It also allows the estimation and visualization of time ranges from the posterior distribution of groups of dates (e.g. duration, transition and hiatus between successive phases) as described in Philippe and Vibet (2020) <doi:10.18637/jss.v093.c01>.

r-aws-ecx 1.0.6
Propagated dependencies: r-xml2@1.5.0 r-rjson@0.2.23 r-httr@1.4.7 r-aws-signature@0.6.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/Jiefei-Wang/aws.ecx
Licenses: GPL 3
Build system: r
Synopsis: Communicating with AWS EC2 and ECS using AWS REST APIs
Description:

Providing the functions for communicating with Amazon Web Services(AWS) Elastic Compute Cloud(EC2) and Elastic Container Service(ECS). The functions will have the prefix ecs_ or ec2_ depending on the class of the API. The request will be sent via the REST API and the parameters are given by the function argument. The credentials can be set via aws_set_credentials'. The EC2 documentation can be found at <https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Welcome.html> and ECS can be found at <https://docs.aws.amazon.com/AmazonECS/latest/APIReference/Welcome.html>.

r-ace-coco 0.1
Propagated dependencies: r-quantreg@6.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/hongyuan-cao/ACE
Licenses: GPL 3
Build system: r
Synopsis: Analysis of Correlated High-Dimensional Expression (ACE) Data
Description:

This package provides a function for estimating factor models. Give factor-adjusted statistics, factor-adjusted mean estimation (one-sample test) or factor-adjusted mean difference estimation (two-sample test).

r-aquadtree 1.0.6
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=AQuadtree
Licenses: Expat
Build system: r
Synopsis: Confidentiality of Spatial Point Data
Description:

This package provides an automatic aggregation tool to manage point data privacy, intended to be helpful for the production of official spatial data and for researchers. The package pursues the data accuracy at the smallest possible areas preventing individual information disclosure. The methodology, based on hierarchical geographic data structures performs aggregation and local suppression of point data to ensure privacy as described in Lagonigro, R., Oller, R., Martori J.C. (2017) <doi:10.2436/20.8080.02.55>. The data structures are created following the guidelines for grid datasets from the European Forum for Geography and Statistics.

r-abjdata 1.1.2
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://abjur.github.io/abjData/
Licenses: Expat
Build system: r
Synopsis: Databases Used Routinely by the Brazilian Jurimetrics Association
Description:

The Brazilian Jurimetrics Association (ABJ in Portuguese, see <https://abj.org.br/> for more information) is a non-profit organization which aims to investigate and promote the use of statistics and probability in the study of Law and its institutions. This package has a set of datasets commonly used in our book.

r-aws-transcribe 0.1.3
Propagated dependencies: r-jsonlite@2.0.0 r-httr@1.4.7 r-aws-signature@0.6.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/cloudyr/aws.transcribe
Licenses: GPL 2+
Build system: r
Synopsis: Client for 'AWS Transcribe'
Description:

Client for AWS Transcribe <https://aws.amazon.com/documentation/transcribe>, a cloud transcription service that can convert an audio media file in English and other languages into a text transcript.

r-ageutils 0.1.2
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://timtaylor.github.io/ageutils/
Licenses: GPL 2
Build system: r
Synopsis: Collection of Functions for Working with Age Intervals
Description:

This package provides a collection of efficient functions for working with individual ages and corresponding intervals. These include functions for conversion from an age to an interval, aggregation of ages with associated counts in to intervals and the splitting of interval counts based on specified age distributions.

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Total results: 69112