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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-densityratio 0.2.2
Propagated dependencies: r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pbapply@1.7-4 r-osqp@0.6.3.3 r-ggplot2@4.0.1 r-ggh4x@0.3.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://thomvolker.github.io/densityratio/
Licenses: GPL 3+
Build system: r
Synopsis: Distribution Comparison Through Density Ratio Estimation
Description:

Fast, flexible and user-friendly tools for distribution comparison through direct density ratio estimation. The estimated density ratio can be used for covariate shift adjustment, outlier-detection, change-point detection, classification and evaluation of synthetic data quality. The package implements multiple non-parametric estimation techniques (unconstrained least-squares importance fitting, ulsif(), Kullback-Leibler importance estimation procedure, kliep(), spectral density ratio estimation, spectral(), kernel mean matching, kmm(), and least-squares hetero-distributional subspace search, lhss()). with automatic tuning of hyperparameters. Helper functions are available for two-sample testing and visualizing the density ratios. For an overview on density ratio estimation, see Sugiyama et al. (2012) <doi:10.1017/CBO9781139035613> for a general overview, and the help files for references on the specific estimation techniques.

r-dccpp 0.1.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://dccpp.berrisch.biz/
Licenses: GPL 3+
Build system: r
Synopsis: Fast Computation of Distance Correlations
Description:

Fast computation of the distance covariance dcov and distance correlation dcor'. The computation cost is only O(n log(n)) for the distance correlation (see Chaudhuri, Hu (2019) <arXiv:1810.11332> <doi:10.1016/j.csda.2019.01.016>). The functions are written entirely in C++ to speed up the computation.

r-demography 2.0.1
Propagated dependencies: r-strucchange@1.5-4 r-rainbow@3.8 r-mgcv@1.9-4 r-hmdhfdplus@2.0.8 r-ftsa@6.6 r-forecast@8.24.0 r-cobs@1.3-9-1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://pkg.robjhyndman.com/demography/
Licenses: GPL 3+
Build system: r
Synopsis: Forecasting Mortality, Fertility, Migration and Population Data
Description:

This package provides functions for demographic analysis including lifetable calculations; Lee-Carter modelling; functional data analysis of mortality rates, fertility rates, net migration numbers; and stochastic population forecasting.

r-dataresqc 1.1.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dataresqc
Licenses: ASL 2.0
Build system: r
Synopsis: C3S Quality Control Tools for Historical Climate Data
Description:

Quality control and formatting tools developed for the Copernicus Data Rescue Service. The package includes functions to handle the Station Exchange Format (SEF), various statistical tests for climate data at daily and sub-daily resolution, as well as functions to plot the data. For more information and documentation see <https://datarescue.climate.copernicus.eu/st_data-quality-control>.

r-didforbigdata 1.0
Propagated dependencies: r-sandwich@3.1-1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://setzler.github.io/DiDforBigData/
Licenses: Expat
Build system: r
Synopsis: Big Data Implementation of Difference-in-Differences Estimation with Staggered Treatment
Description:

This package provides a big-data-friendly and memory-efficient difference-in-differences estimator for staggered (and non-staggered) treatment contexts.

r-deductive 1.0.1
Propagated dependencies: r-validate@1.1.7 r-stringdist@0.9.15 r-lintools@0.1.7
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/data-cleaning/deductive
Licenses: GPL 3
Build system: r
Synopsis: Data Correction and Imputation Using Deductive Methods
Description:

Attempt to repair inconsistencies and missing values in data records by using information from valid values and validation rules restricting the data.

r-dendroanalyst 0.1.5
Propagated dependencies: r-zoo@1.8-14 r-tidyverse@2.0.0 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-readxl@1.4.5 r-pspline@1.0-21 r-minpack-lm@1.2-4 r-mgcv@1.9-4 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-forecast@8.24.0 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=dendRoAnalyst
Licenses: GPL 3
Build system: r
Synopsis: Tool for Processing and Analyzing Dendrometer Data
Description:

There are various functions for managing and cleaning data before the application of different approaches. This includes identifying and erasing sudden jumps in dendrometer data not related to environmental change, identifying the time gaps of recordings, and changing the temporal resolution of data to different frequencies. Furthermore, the package calculates daily statistics of dendrometer data, including the daily amplitude of tree growth. Various approaches can be applied to separate radial growth from daily cyclic shrinkage and expansion due to uptake and loss of stem water. In addition, it identifies periods of consecutive days with user-defined climatic conditions in daily meteorological data, then check what trees are doing during that period.

r-dc3net 1.2.0
Propagated dependencies: r-igraph@2.2.1 r-c3net@1.1.1.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dc3net
Licenses: GPL 3+
Build system: r
Synopsis: Inferring Condition-Specific Networks via Differential Network Inference
Description:

This package performs differential network analysis to infer disease specific gene networks.

r-decomposer 1.0.7
Propagated dependencies: r-usethis@3.2.1 r-tictoc@1.2.1 r-stratigrapher@1.3.1 r-hexbin@1.28.5 r-dplyr@1.1.4 r-colorramps@2.3.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DecomposeR
Licenses: GPL 3
Build system: r
Synopsis: Empirical Mode Decomposition for Cyclostratigraphy
Description:

This package provides tools to apply Ensemble Empirical Mode Decomposition (EEMD) for cyclostratigraphy purposes. Mainly: a new algorithm, extricate, that performs EEMD in seconds, a linear interpolation algorithm using the greatest rational common divisor of depth or time, different algorithms to compute instantaneous amplitude, frequency and ratios of frequencies, and functions to verify and visualise the outputs. The functions were developed during the CRASH project (Checking the Reproducibility of Astrochronology in the Hauterivian). When using for publication please cite Wouters, S., Crucifix, M., Sinnesael, M., Da Silva, A.C., Zeeden, C., Zivanovic, M., Boulvain, F., Devleeschouwer, X., 2022, "A decomposition approach to cyclostratigraphic signal processing". Earth-Science Reviews 225 (103894). <doi:10.1016/j.earscirev.2021.103894>.

r-dann 1.0.2
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-mass@7.3-65 r-hardhat@1.4.2 r-ggplot2@4.0.1 r-fpc@2.2-13
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/gmcmacran/dann
Licenses: Expat
Build system: r
Synopsis: Discriminant Adaptive Nearest Neighbor Classification
Description:

Discriminant Adaptive Nearest Neighbor Classification is a variation of k nearest neighbors where the shape of the neighborhood is data driven. This package implements dann and sub_dann from Hastie (1996) <https://web.stanford.edu/~hastie/Papers/dann_IEEE.pdf>.

r-docorator 0.5.2
Propagated dependencies: r-withr@3.0.2 r-tidyr@1.3.1 r-stringr@1.6.0 r-rstudioapi@0.17.1 r-rmarkdown@2.30 r-rlang@1.1.6 r-quarto@1.5.1 r-purrr@1.2.0 r-png@0.1-8 r-lifecycle@1.0.4 r-knitr@1.50 r-gt@1.3.0 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://GSK-Biostatistics.github.io/docorator/
Licenses: ASL 2.0
Build system: r
Synopsis: Docorate (Decorate + Output) Displays
Description:

This package provides a framework for creating production outputs. Users can frame a table, listing, or figure with headers and footers and save to an output file. Stores an intermediate docorator object for reproducibility and rendering to multiple output types.

r-distrteach 2.9.2
Propagated dependencies: r-startupmsg@1.0.0 r-distrex@2.9.6 r-distr@2.9.7
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: http://distr.r-forge.r-project.org/
Licenses: LGPL 3
Build system: r
Synopsis: Extensions of Package 'distr' for Teaching Stochastics/Statistics in Secondary School
Description:

This package provides flexible examples of LLN and CLT for teaching purposes in secondary school.

r-did 2.3.0
Propagated dependencies: r-tidyr@1.3.1 r-pbapply@1.7-4 r-matrix@1.7-4 r-ggplot2@4.0.1 r-generics@0.1.4 r-fastglm@0.0.3 r-dreamerr@1.5.0 r-drdid@1.2.3 r-data-table@1.17.8 r-bmisc@1.4.8
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://bcallaway11.github.io/did/
Licenses: GPL 2
Build system: r
Synopsis: Treatment Effects with Multiple Periods and Groups
Description:

The standard Difference-in-Differences (DID) setup involves two periods and two groups -- a treated group and untreated group. Many applications of DID methods involve more than two periods and have individuals that are treated at different points in time. This package contains tools for computing average treatment effect parameters in Difference in Differences setups with more than two periods and with variation in treatment timing using the methods developed in Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>. The main parameters are group-time average treatment effects which are the average treatment effect for a particular group at a a particular time. These can be aggregated into a fewer number of treatment effect parameters, and the package deals with the cases where there is selective treatment timing, dynamic treatment effects, calendar time effects, or combinations of these. There are also functions for testing the Difference in Differences assumption, and plotting group-time average treatment effects.

r-dittodb 0.1.11
Propagated dependencies: r-rlang@1.1.6 r-lifecycle@1.0.4 r-glue@1.8.0 r-digest@0.6.39 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://dittodb.jonkeane.com/
Licenses: ASL 2.0
Build system: r
Synopsis: Test Environment for Database Requests
Description:

Testing and documenting code that communicates with remote databases can be painful. Although the interaction with R is usually relatively simple (e.g. data(frames) passed to and from a database), because they rely on a separate service and the data there, testing them can be difficult to set up, unsustainable in a continuous integration environment, or impossible without replicating an entire production cluster. This package addresses that by allowing you to make recordings from your database interactions and then play them back while testing (or in other contexts) all without needing to spin up or have access to the database your code would typically connect to.

r-dppack 0.2.2
Propagated dependencies: r-rmutil@1.1.10 r-rdpack@2.6.4 r-r6@2.6.1 r-nloptr@2.2.1 r-mass@7.3-65 r-ggplot2@4.0.1 r-e1071@1.7-16 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=DPpack
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Differentially Private Statistical Analysis and Machine Learning
Description:

An implementation of common statistical analysis and models with differential privacy (Dwork et al., 2006a) <doi:10.1007/11681878_14> guarantees. The package contains, for example, functions providing differentially private computations of mean, variance, median, histograms, and contingency tables. It also implements some statistical models and machine learning algorithms such as linear regression (Kifer et al., 2012) <https://proceedings.mlr.press/v23/kifer12.html> and SVM (Chaudhuri et al., 2011) <https://jmlr.org/papers/v12/chaudhuri11a.html>. In addition, it implements some popular randomization mechanisms, including the Laplace mechanism (Dwork et al., 2006a) <doi:10.1007/11681878_14>, Gaussian mechanism (Dwork et al., 2006b) <doi:10.1007/11761679_29>, analytic Gaussian mechanism (Balle & Wang, 2018) <https://proceedings.mlr.press/v80/balle18a.html>, and exponential mechanism (McSherry & Talwar, 2007) <doi:10.1109/FOCS.2007.66>.

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-daly 1.5.0
Dependencies: tcl@8.6.12
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: http://daly.cbra.be
Licenses: GPL 2+
Build system: r
Synopsis: The DALY Calculator - Graphical User Interface for Probabilistic DALY Calculation in R
Description:

The DALY Calculator is a free, open-source Graphical User Interface (GUI) for stochastic disability-adjusted life year (DALY) calculation.

r-dlpca 0.0.5
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DLPCA
Licenses: Expat
Build system: r
Synopsis: The Distributed Local PCA Algorithm
Description:

Algorithm to handle with optimal subset selection for distributed local principal component analysis. The philosophy of the package is described in Guo G. (2020) <doi:10.1080/02331888.2020.1823979>.

r-dcm2 1.0.2
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-modelr@0.1.11 r-magrittr@2.0.4 r-glue@1.8.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/atlas-aai/dcm2
Licenses: GPL 3
Build system: r
Synopsis: Calculating the M2 Model Fit Statistic for Diagnostic Classification Models
Description:

This package provides a collection of functions for calculating the M2 model fit statistic for diagnostic classification models as described by Liu et al. (2016) <DOI:10.3102/1076998615621293>. These functions provide multiple sources of information for model fit according to the M2 statistic, including the M2 statistic, the *p* value for that M2 statistic, and the Root Mean Square Error of Approximation based on the M2 statistic.

r-datastat 0.1.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=datastat
Licenses: CC0
Build system: r
Synopsis: Dataset for Statistical Analysis
Description:

Data are essential in statistical analysis. This data package consists of four datasets for descriptive statistics, two datasets for statistical hypothesis testing, and two datasets for regression analysis. All of the datasets are based on Rattanalertnusorn, A. (2024) <https://www.researchgate.net/publication/371944275_porkaermxarlaeakarprayuktchingan_R_and_its_applications>.

r-ds4psy 1.2.0
Propagated dependencies: r-unikn@1.0.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://bookdown.org/hneth/ds4psy/
Licenses: CC-BY-SA 4.0
Build system: r
Synopsis: Data Science for Psychologists
Description:

All datasets and functions required for the examples and exercises of the book "Data Science for Psychologists" (by Hansjoerg Neth, Konstanz University, 2025, <doi:10.5281/zenodo.7229812>), freely available at <https://bookdown.org/hneth/ds4psy/>. The book and corresponding courses introduce principles and methods of data science to students of psychology and other biological or social sciences. The ds4psy package primarily provides datasets, but also functions for data generation and manipulation (e.g., of text and time data) and graphics that are used in the book and its exercises. All functions included in ds4psy are designed to be explicit and instructive, rather than efficient or elegant.

r-dbnmfrank 0.1.0
Propagated dependencies: r-pmledecon@0.2.1 r-nmf@0.28
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DBNMFrank
Licenses: GPL 3+
Build system: r
Synopsis: Rank Selection for Non-Negative Matrix Factorization
Description:

Given the non-negative data and its distribution, the package estimates the rank parameter for Non-negative Matrix Factorization. The method is based on hypothesis testing, using a deconvolved bootstrap distribution to assess the significance level accurately despite the large amount of optimization error. The distribution of the non-negative data can be either Normal distributed or Poisson distributed.

r-delta 0.2.0.3
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=Delta
Licenses: GPL 3
Build system: r
Synopsis: Measure of Agreement Between Two Raters
Description:

Measure of agreement delta was originally by Martà n & Femia (2004) <DOI:10.1348/000711004849268>. Since then has been considered as agreement measure for different fields, since their behavior is usually better than the usual kappa index by Cohen (1960) <DOI:10.1177/001316446002000104>. The main issue with delta is that can not be computed by hand contrary to kappa. The current algorithm is based on the Version 5 of the delta windows program that can be found on <https://www.ugr.es/~bioest/software/delta/cmd.php?seccion=downloads>.

r-debar 0.1.1
Propagated dependencies: r-seqinr@4.2-36 r-aphid@1.3.6 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=debar
Licenses: GPL 3
Build system: r
Synopsis: Post-Clustering Denoiser for COI-5P Barcode Data
Description:

The debar sequence processing pipeline is designed for denoising high throughput sequencing data for the animal DNA barcode marker cytochrome c oxidase I (COI). The package is designed to detect and correct insertion and deletion errors within sequencer outputs. This is accomplished through comparison of input sequences against a profile hidden Markov model (PHMM) using the Viterbi algorithm (for algorithm details see Durbin et al. 1998, ISBN: 9780521629713). Inserted base pairs are removed and deleted base pairs are accounted for through the introduction of a placeholder character. Since the PHMM is a probabilistic representation of the COI barcode, corrections are not always perfect. For this reason debar censors base pairs adjacent to reported indel sites, turning them into placeholder characters (default is 7 base pairs in either direction, this feature can be disabled). Testing has shown that this censorship results in the correct sequence length being restored, and erroneous base pairs being masked the vast majority of the time (>95%).

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