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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-inferencesmr 1.0.2
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=InferenceSMR
Licenses: GPL 2+
Build system: r
Synopsis: Inference About the Standardized Mortality Ratio when Evaluating the Effect of a Screening Program on Survival
Description:

This package provides functions to make inference about the standardized mortality ratio (SMR) when evaluating the effect of a screening program. The package is based on methods described in Sasieni (2003) <doi: 10.1097/00001648-200301000-00026> and Talbot et al. (2011) <doi: 10.1002/sim.4334>.

r-indexwizard 0.2.1.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/johannesgeibel/IndexWizard
Licenses: Expat
Build system: r
Synopsis: Constructing and Analyzing Complex Selection Indices
Description:

Allows the construction selection indices based on estimated breeding values in animal and plant breeding and to calculate several analytic measures around to assess its impact on genetic and phenotypic progress. The methodology thereby allows to analyze genetic gain of traits in the breeding goal which are not part of the actual index and automatically computes several analytic measures. It further allows to retrospectively derive realized economic weights from observed genetic trends. The framework is described in Simianer, H., Heise, J., Rensing, S., Pook, T. Geibel, J. and Reimer, C. (2023) <doi:10.1186/s12711-023-00807-0>.

r-incidental 0.1
Propagated dependencies: r-numderiv@2016.8-1.1 r-matrixstats@1.5.0 r-mass@7.3-65 r-ggplot2@4.0.1 r-dlnm@2.4.10
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=incidental
Licenses: Expat
Build system: r
Synopsis: Implements Empirical Bayes Incidence Curves
Description:

Make empirical Bayes incidence curves from reported case data using a specified delay distribution.

r-insect 1.4.4
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/shaunpwilkinson/insect
Licenses: GPL 3
Build system: r
Synopsis: Informatic Sequence Classification Trees
Description:

This package provides tools for probabilistic taxon assignment with informatic sequence classification trees. See Wilkinson et al (2018) <doi:10.7287/peerj.preprints.26812v1>.

r-isat 1.0.5
Propagated dependencies: r-stringr@1.6.0 r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ISAT
Licenses: GPL 2
Build system: r
Synopsis: Extract Cell Density and Nearest Distance Based on 'PerkinElmer InForm' Software Output
Description:

Reads the output of the PerkinElmer InForm software <http://www.perkinelmer.com/product/inform-cell-analysis-one-seat-cls135781>. In addition to cell-density count, it can derive statistics of intercellular spatial distance for each cell-type.

r-ideamdb 0.0.9
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ideamdb
Licenses: GPL 2+
Build system: r
Synopsis: Easy Manipulation of IDEAM's Climatological Data
Description:

Time series plain text conversion and data visualization. It allows to transform IDEAM (Instituto de Hidrologia, Meteorologia y Estudios Ambientales) daily series from plain text to CSV files or data frames in R. Additionally, it is possible to obtain exploratory graphs from times series. IDEAMâ s data is freely delivered under formal request through the official web page <http://www.ideam.gov.co/solicitud-de-informacion>.

r-isetools 3.2.1
Propagated dependencies: r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ISEtools
Licenses: GPL 2
Build system: r
Synopsis: Ion Selective Electrodes Analysis Methods
Description:

Characterisation and calibration of single or multiple Ion Selective Electrodes (ISEs); activity estimation of experimental samples. Implements methods described in: Dillingham, P.W., Radu, T., Diamond, D., Radu, A. and McGraw, C.M. (2012) <doi:10.1002/elan.201100510>, Dillingham, P.W., Alsaedi, B.S.O. and McGraw, C.M. (2017) <doi:10.1109/ICSENS.2017.8233898>, Dillingham, P.W., Alsaedi, B.S.O., Radu, A., and McGraw, C.M. (2019) <doi:10.3390/s19204544>, and Dillingham, P.W., Alsaedi, B.S.O., Granados-Focil, S., Radu, A., and McGraw, C.M. (2020) <doi:10.1021/acssensors.9b02133>.

r-iron 0.1.5
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/nunompmoniz/IRon
Licenses: CC0
Build system: r
Synopsis: Solving Imbalanced Regression Tasks
Description:

Imbalanced domain learning has almost exclusively focused on solving classification tasks, where the objective is to predict cases labelled with a rare class accurately. Such a well-defined approach for regression tasks lacked due to two main factors. First, standard regression tasks assume that each value is equally important to the user. Second, standard evaluation metrics focus on assessing the performance of the model on the most common cases. This package contains methods to tackle imbalanced domain learning problems in regression tasks, where the objective is to predict extreme (rare) values. The methods contained in this package are: 1) an automatic and non-parametric method to obtain such relevance functions; 2) visualisation tools; 3) suite of evaluation measures for optimisation/validation processes; 4) the squared-error relevance area measure, an evaluation metric tailored for imbalanced regression tasks. More information can be found in Ribeiro and Moniz (2020) <doi:10.1007/s10994-020-05900-9>.

r-intervcomp 0.1.2
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=intervcomp
Licenses: GPL 3
Build system: r
Synopsis: Hypothesis Testing Using the Overlapping Interval Estimates
Description:

This package performs hypothesis testing using the interval estimates (e.g., confidence intervals). The non-overlapping interval estimates indicates the statistical significance. References to these procedures can be found at Noguchi and Marmolejo-Ramos (2016) <doi:10.1080/00031305.2016.1200487>, Bonett and Seier (2003) <doi:10.1198/0003130032323>, and Lemm (2006) <doi:10.1300/J082v51n02_05>.

r-ivmodel 1.9.1
Propagated dependencies: r-reshape2@1.4.5 r-matrix@1.7-4 r-ggplot2@4.0.1 r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ivmodel
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: Statistical Inference and Sensitivity Analysis for Instrumental Variables Model
Description:

Carries out instrumental variable estimation of causal effects, including power analysis, sensitivity analysis, and diagnostics. See Kang, Jiang, Zhao, and Small (2020) <http://pages.cs.wisc.edu/~hyunseung/> for details.

r-imputemissings 0.0.4
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=imputeMissings
Licenses: GPL 2+
Build system: r
Synopsis: Impute Missing Values in a Predictive Context
Description:

Compute missing values on a training data set and impute them on a new data set. Current available options are median/mode and random forest.

r-ifp 0.2.4
Propagated dependencies: r-haplo-stats@1.9.7 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://www.r-project.org
Licenses: GPL 2+
Build system: r
Synopsis: Identifying Functional Polymorphisms
Description:

This package provides a suite for identifying causal models using relative concordances and identifying causal polymorphisms in case-control genetic association data, especially with large controls re-sequenced data.

r-ineqjd 1.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ineqJD
Licenses: GPL 2+
Build system: r
Synopsis: Inequality Joint Decomposition
Description:

Computes and decomposes Gini, Bonferroni and Zenga 2007 point and synthetic concentration indexes. Decompositions are intended: by sources, by subpopulations and by sources and subpopulations jointly. References, Zenga M. M.(2007) <doi:10.1400/209575> Zenga M. (2015) <doi:10.1400/246627> Zenga M., Valli I. (2017) <doi:10.26350/999999_000005> Zenga M., Valli I. (2018) <doi:10.26350/999999_000011>.

r-ivgets 0.1.2
Propagated dependencies: r-stringr@1.6.0 r-ivreg@0.6-7 r-gets@0.38
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/jkurle/ivgets
Licenses: GPL 3+
Build system: r
Synopsis: General to Specific Modeling and Indicator Saturation in 2SLS Models
Description:

This package provides facilities of general to specific model selection for exogenous regressors in 2SLS models. Furthermore, indicator saturation methods can be used to detect outliers and structural breaks in the sample.

r-ical 0.1.6
Propagated dependencies: r-v8@8.0.1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ical
Licenses: Expat
Build system: r
Synopsis: 'iCalendar' Parsing
Description:

This package provides a simple wrapper around the ical.js library executing Javascript code via V8 (the Javascript engine driving the Chrome browser and Node.js and accessible via the V8 R package). This package enables users to parse iCalendar files ('.ics', .ifb', .iCal', .iFBf') into lists and data.frames to ultimately do statistics on events, meetings, schedules, birthdays, and the like.

r-incidenceprevalence 1.2.1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://darwin-eu.github.io/IncidencePrevalence/
Licenses: FSDG-compatible
Build system: r
Synopsis: Estimate Incidence and Prevalence using the OMOP Common Data Model
Description:

Calculate incidence and prevalence using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. Incidence and prevalence can be estimated for the total population in a database or for a stratification cohort.

r-ipec 1.1.2
Propagated dependencies: r-numderiv@2016.8-1.1 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=IPEC
Licenses: GPL 2+
Build system: r
Synopsis: Root Mean Square Curvature Calculation
Description:

Calculates the RMS intrinsic and parameter-effects curvatures of a nonlinear regression model. The curvatures are global measures of assessing whether a model/data set combination is close-to-linear or not. See Bates and Watts (1980) <doi:10.1002/9780470316757> and Ratkowsky and Reddy (2017) <doi:10.1093/aesa/saw098> for details.

r-insurancedata 1.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=insuranceData
Licenses: GPL 2
Build system: r
Synopsis: Collection of Insurance Datasets Useful in Risk Classification in Non-life Insurance.
Description:

Insurance datasets, which are often used in claims severity and claims frequency modelling. It helps testing new regression models in those problems, such as GLM, GLMM, HGLM, non-linear mixed models etc. Most of the data sets are applied in the project "Mixed models in ratemaking" supported by grant NN 111461540 from Polish National Science Center.

r-iscores 1.1.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=Iscores
Licenses: GPL 3
Build system: r
Synopsis: Proper Scoring Rules for Missing Value Imputation
Description:

Implementation of a KL-based scoring rule to assess the quality of different missing value imputations in the broad sense as introduced in Michel et al. (2021) <arXiv:2106.03742>.

r-icesat2r 1.0.9
Propagated dependencies: r-withr@3.0.2 r-units@1.0-0 r-shiny@1.11.1 r-sf@1.0-23 r-rvest@1.0.5 r-rnaturalearth@1.1.0 r-miniui@0.1.2 r-magrittr@2.0.4 r-lwgeom@0.2-14 r-lubridate@1.9.4 r-leafsync@0.1.0 r-leaflet@2.2.3 r-leafgl@0.2.2 r-httr@1.4.7 r-htmlwidgets@1.6.4 r-htmltools@0.5.8.1 r-glue@1.8.0 r-foreach@1.5.2 r-doparallel@1.0.17 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/mlampros/IceSat2R
Licenses: GPL 3
Build system: r
Synopsis: 'ICESat-2' Altimeter Data using R
Description:

Programmatic connection to the OpenAltimetry API <https://openaltimetry.earthdatacloud.nasa.gov/data/openapi/swagger-ui/index.html/> to download and process ATL03 (Global Geolocated Photon Data), ATL06 (Land Ice Height), ATL07 (Sea Ice Height), ATL08 (Land and Vegetation Height), ATL10 (Sea Ice Freeboard'), ATL12 (Ocean Surface Height) and ATL13 (Inland Water Surface Height) ICESat-2 Altimeter Data. The user has the option to download the data by selecting a bounding box from a 1- or 5-degree grid globally utilizing a shiny application. The ICESat-2 mission collects altimetry data of the Earth's surface. The sole instrument on ICESat-2 is the Advanced Topographic Laser Altimeter System (ATLAS) instrument that measures ice sheet elevation change and sea ice thickness, while also generating an estimate of global vegetation biomass. ICESat-2 continues the important observations of ice-sheet elevation change, sea-ice freeboard', and vegetation canopy height begun by ICESat in 2003.

r-ibcf-mtme 1.6-0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/frahik/IBCF.MTME
Licenses: LGPL 3
Build system: r
Synopsis: Item Based Collaborative Filtering for Multi-Trait and Multi-Environment Data
Description:

This package implements the item based collaborative filtering (IBCF) method for continues phenotypes in the context of plant breeding where data are collected for various traits that were studied in various environments proposed by Montesinos-López et al. (2017) <doi:10.1534/g3.117.300309>.

r-interpretmsspectrum 1.5.2
Propagated dependencies: r-plyr@1.8.9 r-envipat@2.8
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/janlisec/InterpretMSSpectrum
Licenses: GPL 3
Build system: r
Synopsis: Interpreting High Resolution Mass Spectra
Description:

High resolution mass spectrometry yields often large data sets of spectra from compounds which are not present in available libraries. These spectra need to be annotated and interpreted. InterpretMSSpectrum provides a set of functions to perform such tasks for Electrospray-Ionization and Atmospheric-Pressure-Chemical-Ionization derived data in positive and negative ionization mode.

r-icc 2.4.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/matthewwolak/ICC
Licenses: GPL 2+
Build system: r
Synopsis: Facilitating Estimation of the Intraclass Correlation Coefficient
Description:

Assist in the estimation of the Intraclass Correlation Coefficient (ICC) from variance components of a one-way analysis of variance and also estimate the number of individuals or groups necessary to obtain an ICC estimate with a desired confidence interval width.

r-ipmrf 1.3
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=IPMRF
Licenses: GPL 3
Build system: r
Synopsis: Intervention in Prediction Measure for Random Forests
Description:

Computes intervention in prediction measure for assessing variable importance for random forests. See details at I. Epifanio (2017) <DOI:10.1186/s12859-017-1650-8>.

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