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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-deeptimedata 1.0.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: http://williamgearty.com/deeptimedata/
Licenses: GPL 3+
Build system: r
Synopsis: Geologic Pattern Data from FGDC Used in 'deeptime'
Description:

Geologic pattern data from <https://ngmdb.usgs.gov/fgdc_gds/geolsymstd.php>. Access functions are provided in the accompanying package deeptime'.

r-dynrb 0.19
Propagated dependencies: r-vegan@2.7-2 r-reshape2@1.4.5 r-rcolorbrewer@1.1-3 r-ggplot2@4.0.1 r-foreign@0.8-90 r-dplyr@1.1.4 r-corrplot@0.95
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dynRB
Licenses: GPL 2
Build system: r
Synopsis: Dynamic Range Boxes
Description:

Improves the concept of multivariate range boxes, which is highly susceptible for outliers and does not consider the distribution of the data. The package uses dynamic range boxes to overcome these problems.

r-datacutr 0.2.4
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-reactable@0.4.5 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-dplyr@1.1.4 r-assertthat@0.2.1 r-admiraldev@1.4.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://pharmaverse.github.io/datacutr/
Licenses: FSDG-compatible
Build system: r
Synopsis: SDTM Datacut
Description:

Supports the process of applying a cut to Standard Data Tabulation Model (SDTM), as part of the analysis of specific points in time of the data, normally as part of investigation into clinical trials. The functions support different approaches of cutting to the different domains of SDTM normally observed.

r-drugutilisation 1.1.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-patientprofiles@1.5.0 r-omopgenerics@1.3.7 r-lifecycle@1.0.4 r-glue@1.8.0 r-dplyr@1.1.4 r-codelistgenerator@4.0.2 r-clock@0.7.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://darwin-eu.github.io/DrugUtilisation/
Licenses: FSDG-compatible
Build system: r
Synopsis: Summarise Patient-Level Drug Utilisation in Data Mapped to the OMOP Common Data Model
Description:

Summarise patient-level drug utilisation cohorts using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. New users and prevalent users cohorts can be generated and their characteristics, indication and drug use summarised.

r-difboost 0.4
Propagated dependencies: r-stabs@0.6-4 r-penalized@0.9-53 r-mboost@2.9-11
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DIFboost
Licenses: GPL 2
Build system: r
Synopsis: Detection of Differential Item Functioning (DIF) in Rasch Models by Boosting Techniques
Description:

This package performs detection of Differential Item Functioning using the method DIFboost as proposed by Schauberger and Tutz (2016) <doi:10.1111/bmsp.12060>.

r-doofa 1.0
Propagated dependencies: r-lpsolve@5.6.23 r-combinat@0.0-8
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=doofa
Licenses: GPL 2+
Build system: r
Synopsis: Designs for Order-of-Addition Experiments
Description:

This package provides a facility to generate efficient designs for order-of-additions experiments under pair-wise-order model, see Dennis K. J. Lin and Jiayu Peng (2019)."Order-of-addition experiments: A review and some new thoughts". Quality Engineering, 31:1, 49-59, <doi:10.1080/08982112.2018.1548021>. It also provides a facility to generate component orthogonal arrays under component position model, see Jian-Feng Yang, Fasheng Sun & Hongquan Xu (2020): "A Component Position Model, Analysis and Design for Order-of-Addition Experiments". Technometrics, <doi:10.1080/00401706.2020.1764394>.

r-dycdtools 0.4.4
Propagated dependencies: r-tidyr@1.3.1 r-rcolorbrewer@1.1-3 r-r-utils@2.13.0 r-ncdf4@1.24 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/SongyanYu/dycdtools
Licenses: Expat
Build system: r
Synopsis: Calibration Assistant and Post-Processing Tool for Aquatic Ecosystem Model DYRESM-CAEDYM
Description:

Dynamic Reservoir Simulation Model (DYRESM) and Computational Aquatic Ecosystem Dynamics Model (CAEDYM) model development, including assisting with calibrating selected model parameters and visualising model output through time series plot, profile plot, contour plot, and scatter plot. For more details, see Yu et al. (2023) <https://journal.r-project.org/articles/RJ-2023-008/>.

r-dstem 2.0-1
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://doi.org/10.1214/20-EJS1751
Licenses: GPL 3
Build system: r
Synopsis: Multiple Testing of Local Extrema for Detection of Change Points
Description:

Simultaneously detect the number and locations of change points in piecewise linear models under stationary Gaussian noise allowing autocorrelated random noise. The core idea is to transform the problem of detecting change points into the detection of local extrema (local maxima and local minima)through kernel smoothing and differentiation of the data sequence, see Cheng et al. (2020) <doi:10.1214/20-EJS1751>. A low-computational and fast algorithm call dSTEM is introduced to detect change points based on the STEM algorithm in D. Cheng and A. Schwartzman (2017) <doi:10.1214/16-AOS1458>.

r-dipw 0.1.0
Propagated dependencies: r-rmosek@1.3.5 r-matrix@1.7-4 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dipw
Licenses: GPL 3
Build system: r
Synopsis: Debiased Inverse Propensity Score Weighting
Description:

Estimation of the average treatment effect when controlling for high-dimensional confounders using debiased inverse propensity score weighting (DIPW). DIPW relies on the propensity score following a sparse logistic regression model, but the regression curves are not required to be estimable. Despite this, our package also allows the users to estimate the regression curves and take the estimated curves as input to our methods. Details of the methodology can be found in Yuhao Wang and Rajen D. Shah (2020) "Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders" <arXiv:2011.08661>. The package relies on the optimisation software MOSEK <https://www.mosek.com/> which must be installed separately; see the documentation for Rmosek'.

r-dtcompair 1.2.6
Propagated dependencies: r-propcis@0.3-0 r-gee@4.13-29 r-ellipse@0.5.0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/chstock/DTComPair
Licenses: GPL 3+
Build system: r
Synopsis: Comparison of Binary Diagnostic Tests in a Paired Study Design
Description:

Comparison of the accuracy of two binary diagnostic tests in a "paired" study design, i.e. when each test is applied to each subject in the study.

r-deconvolver 1.2-1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://bnaras.github.io/deconvolveR/
Licenses: GPL 2+
Build system: r
Synopsis: Empirical Bayes Estimation Strategies
Description:

Empirical Bayes methods for learning prior distributions from data. An unknown prior distribution (g) has yielded (unobservable) parameters, each of which produces a data point from a parametric exponential family (f). The goal is to estimate the unknown prior ("g-modeling") by deconvolution and Empirical Bayes methods. Details and examples are in the paper by Narasimhan and Efron (2020, <doi:10.18637/jss.v094.i11>).

r-ddhfm 1.1.4
Propagated dependencies: r-wavethresh@4.7.3 r-lokern@1.1-12
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DDHFm
Licenses: GPL 2
Build system: r
Synopsis: Variance Stabilization by Data-Driven Haar-Fisz (for Microarrays)
Description:

This package contains the normalizing and variance stabilizing Data-Driven Haar-Fisz algorithm. Also contains related algorithms for simulating from certain microarray gene intensity models and evaluation of certain transformations. Contains cDNA and shipping credit flow data.

r-datamedios 1.2.2
Propagated dependencies: r-xml2@1.5.0 r-wordcloud2@0.2.1 r-tidytext@0.4.3 r-stringr@1.6.0 r-rvest@1.0.5 r-rlang@1.1.6 r-purrr@1.2.0 r-plotly@4.11.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-ggplot2@4.0.1 r-dt@0.34.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=datamedios
Licenses: Expat
Build system: r
Synopsis: Scraping Chilean Media
Description:

This package provides a system for extracting news from Chilean media, specifically through Web Scapping from Chilean media. The package allows for news searches using search phrases and date filters, and returns the results in a structured format, ready for analysis. Additionally, it includes functions to clean the extracted data, visualize it, and store it in databases. All of this can be done automatically, facilitating the collection and analysis of relevant information from Chilean media.

r-dr4pl 2.0.0
Propagated dependencies: r-tensor@1.5.1 r-rlang@1.1.6 r-rdpack@2.6.4 r-matrix@1.7-4 r-glue@1.8.0 r-ggplot2@4.0.1 r-generics@0.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://bitbucket.org/dittmerlab/dr4pl
Licenses: GPL 2+
Build system: r
Synopsis: Dose Response Data Analysis using the 4 Parameter Logistic (4pl) Model
Description:

Models the relationship between dose levels and responses in a pharmacological experiment using the 4 Parameter Logistic model. Traditional packages on dose-response modelling such as drc and nplr often draw errors due to convergence failure especially when data have outliers or non-logistic shapes. This package provides robust estimation methods that are less affected by outliers and other initialization methods that work well for data lacking logistic shapes. We provide the bounds on the parameters of the 4PL model that prevent parameter estimates from diverging or converging to zero and base their justification in a statistical principle. These methods are used as remedies to convergence failure problems. Gadagkar, S. R. and Call, G. B. (2015) <doi:10.1016/j.vascn.2014.08.006> Ritz, C. and Baty, F. and Streibig, J. C. and Gerhard, D. (2015) <doi:10.1371/journal.pone.0146021>.

r-descomponer 1.6
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=descomponer
Licenses: GPL 2+
Build system: r
Synopsis: Seasonal Adjustment by Frequency Analysis
Description:

Decompose a time series into seasonal, trend and irregular components using transformations to amplitude-frequency domain.

r-dicem 0.1.0
Propagated dependencies: r-xgboost@1.7.11.1 r-vader@0.2.1 r-stringr@1.6.0 r-quanteda@4.3.1 r-politeness@0.9.4 r-matrix@1.7-4 r-doc2concrete@0.6.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DICEM
Licenses: Expat
Build system: r
Synopsis: Directness and Intensity of Conflict Expression
Description:

This package provides a Natural Language Processing Model trained to detect directness and intensity during conflict. See <https://www.mikeyeomans.info>.

r-dtmapi 0.1.0
Propagated dependencies: r-testthat@3.3.0 r-httr2@1.2.1 r-askpass@1.2.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/Displacement-Tracking-Matrix/dtmapi-R
Licenses: Expat
Build system: r
Synopsis: Fetching Data from the 'Displacement Tracking Matrix'
Description:

Allows humanitarian community, academia, media, government, and non-governmental organizations to utilize the data collected by the Displacement Tracking Matrix (<https://dtm.iom.int>), a unit in the International Organization for Migration. This also provides non-sensitive Internally Displaced Person figures, aggregated at the country, Admin 1 (states, provinces, or equivalent), and Admin 2 (smaller administrative areas) levels.

r-duawranglr 0.6.7
Propagated dependencies: r-readxl@1.4.5 r-readr@2.1.6 r-haven@2.5.5 r-dplyr@1.1.4 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/btskinner/duawranglr
Licenses: Expat
Build system: r
Synopsis: Securely Wrangle Dataset According to Data Usage Agreement
Description:

Create shareable data sets from raw data files that contain protected elements. Relying on master crosswalk files that list restricted variables, package functions warn users about possible violations of data usage agreement and prevent writing protected elements.

r-denvax 0.1.2
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://gitlab.com/cabp_LSHTM/denvax
Licenses: Expat
Build system: r
Synopsis: Simple Dengue Test and Vaccinate Cost Thresholds
Description:

This package provides the mathematical model described by "Serostatus Testing & Dengue Vaccine Cost-Benefit Thresholds" in <doi:10.1098/rsif.2019.0234>. Using the functions in the package, that analysis can be repeated using sample life histories, either synthesized from local seroprevalence data using other functions in this package (as in the manuscript) or from some other source. The package provides a vignette which walks through the analysis in the publication, as well as a function to generate a project skeleton for such an analysis.

r-design-parameters 0.1.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=Design.parameters
Licenses: GPL 3
Build system: r
Synopsis: Parameters of the Experimental Designs
Description:

Here, a function has been developed to generate parameters of the input designs, as well as incidence matrices. This is a general function that can be used to investigate the characterization properties of any block design.

r-datasda 0.1.8
Propagated dependencies: r-tidyr@1.3.1 r-rsda@3.2.5 r-magrittr@2.0.4 r-histdawass@1.0.8 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dataSDA
Licenses: GPL 2+
Build system: r
Synopsis: Datasets and Basic Statistics for Symbolic Data Analysis
Description:

Collects a diverse range of symbolic data and offers a comprehensive set of functions that facilitate the conversion of traditional data into the symbolic data format.

r-dyads 1.2.1
Propagated dependencies: r-rfast@2.1.5.2 r-rcppziggurat@0.1.8 r-mvtnorm@1.3-3 r-mass@7.3-65 r-cholwishart@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dyads
Licenses: GPL 2+
Build system: r
Synopsis: Dyadic Network Analysis
Description:

This package contains functions for the MCMC simulation of dyadic network models j2 (Zijlstra, 2017, <doi:10.1080/0022250X.2017.1387858>) and p2 (Van Duijn, Snijders & Zijlstra, 2004, <doi: 10.1046/j.0039-0402.2003.00258.x>), the multilevel p2 model (Zijlstra, Van Duijn & Snijders (2009) <doi: 10.1348/000711007X255336>), and the bidirectional (multilevel) counterpart of the the multilevel p2 model as described in Zijlstra, Van Duijn & Snijders (2009) <doi: 10.1348/000711007X255336>, the (multilevel) b2 model.

r-dstat 1.0.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dstat
Licenses: GPL 2
Build system: r
Synopsis: Conditional Sensitivity Analysis for Matched Observational Studies
Description:

This package provides a d-statistic tests the null hypothesis of no treatment effect in a matched, nonrandomized study of the effects caused by treatments. A d-statistic focuses on subsets of matched pairs that demonstrate insensitivity to unmeasured bias in such an observational study, correcting for double-use of the data by conditional inference. This conditional inference can, in favorable circumstances, substantially increase the power of a sensitivity analysis (Rosenbaum (2010) <doi:10.1007/978-1-4419-1213-8_14>). There are two examples, one concerning unemployment from Lalive et al. (2006) <doi:10.1111/j.1467-937X.2006.00406.x>, the other concerning smoking and periodontal disease from Rosenbaum (2017) <doi:10.1214/17-STS621>.

r-directeffects 0.3
Propagated dependencies: r-rlang@1.1.6 r-matching@4.10-15 r-glue@1.8.0 r-generics@0.1.4 r-formula@1.2-5 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://mattblackwell.github.io/DirectEffects/
Licenses: GPL 2+
Build system: r
Synopsis: Estimating Controlled Direct Effects for Explaining Causal Findings
Description:

This package provides a set of functions to estimate the controlled direct effect of treatment fixing a potential mediator to a specific value. Implements the sequential g-estimation estimator described in Vansteelandt (2009) <doi:10.1097/EDE.0b013e3181b6f4c9> and Acharya, Blackwell, and Sen (2016) <doi:10.1017/S0003055416000216> and the telescope matching estimator described in Blackwell and Strezhnev (2020) <doi:10.1111/rssa.12759>.

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