This is a package for saving matrices, arrays and similar objects into file artifacts, and loading them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

eval-in-repl provides a consistent ESS-like evaluation interface for various REPLs. In particular, it mimics ESS' C-RET binding, which sends a line or region to an appropriately configured shell. This package provides just the core of eval-in-repl---for the languages themselves, see their respective packages.

Adjust the Gamma regression models from a Bayesian perspective described by Cepeda and Urdinola (2012) <doi:10.1080/03610918.2011.600500>, modeling the parameters of mean and shape and using different link functions for the parameter associated to the mean. And calculates different adjustment statistics such as the Akaike information criterion and Bayesian information criterion.

Estimation of optimal portfolio weights as combination of simple portfolio strategies, like the tangency, global minimum variance (GMV) or naive (1/N) portfolio. It is based on a utility maximizing 8-fund rule. Popular special cases like the Kan-Zhou(2007) 2-fund and 3-fund rule or the Tu-Zhou(2011) estimator are nested.

This package provides a quasiquoter for raw string literals, i.e. string literals that don't recognise the standard escape sequences. Basically, they make your code more readable by freeing you from the responsibility to escape backslashes. They are useful when working with regular expressions, DOS/Windows paths and markup languages (such as XML).

This module exports a single hash (%RE) that stores or generates commonly needed regular expressions. Patterns currently provided include: balanced parentheses and brackets, delimited text (with escapes), integers and floating-point numbers in any base (up to 36), comments in 44 languages, offensive language, lists of any pattern, IPv4 addresses, URIs, and Zip codes.

This package provides a collection of functions to set up Google Public Data Explorer <https://www.google.com/publicdata/> data visualization tool with your own data, building automatically the corresponding DataSet Publishing Language file, or DSPL (XML), metadata file jointly with the CSV files. All zip-up and ready to be published in Public Data Explorer'.

Local structure in genomic data often induces dependence between observations taken at different genomic locations. Ignoring this dependence leads to underestimation of the standard error of parameter estimates. This package uses block bootstrapping to estimate asymptotically correct standard errors of parameters from any standard generalised linear model that may be fit by the glm() function.

Ensemble functions for outlier/anomaly detection. There is a new ensemble method proposed using Item Response Theory. Existing outlier ensemble methods from Schubert et al (2012) <doi:10.1137/1.9781611972825.90>, Chiang et al (2017) <doi:10.1016/j.jal.2016.12.002> and Aggarwal and Sathe (2015) <doi:10.1145/2830544.2830549> are also included.

Scraping content from archived web pages stored in the Internet Archive (<https://archive.org>) using a systematic workflow. Get an overview of the mementos available from the respective homepage, retrieve the Urls and links of the page and finally scrape the content. The final output is stored in tibbles, which can be then easily used for further analysis.

You can apply image processing effects that modifies the perceived material properties of objects in photos, such as gloss, smoothness, and blemishes. This is an implementation of the algorithm proposed by Boyadzhiev et al. (2015) "Band-Sifting Decomposition for Image Based Material Editing". Documentation and practical tips of the package is available at <https://github.com/tsuda16k/materialmodifier>.

Extract the signed backbones of intrinsically dense weighted networks based on the significance filter and vigor filter as described in the following paper. Please cite it if you find this software useful in your work. Furkan Gursoy and Bertan Badur. "Extracting the signed backbone of intrinsically dense weighted networks." Journal of Complex Networks. <arXiv:2012.05216>.

This package provides a curated dataset of publicly available ChIP-sequencing of transcription factors, chromatin remodelers and histone modifications in the 3T3-L1 pre-adipocyte cell line. The package document the data collection, pre-processing and processing of the data. In addition to the documentation, the package contains the scripts that was used to generated the data.

Flask-RESTX is an extension for Flask that adds support for quickly building REST APIs. Flask-RESTX encourages best practices with minimal setup. If you are familiar with Flask, Flask-RESTX should be easy to pick up. It provides a coherent collection of decorators and tools to describe your API and expose its documentation properly using Swagger.

Visualize clonal expansion via circle-packing. APackOfTheClones extends scRepertoire to produce a publication-ready visualization of clonal expansion at a single cell resolution, by representing expanded clones as differently sized circles. The method was originally implemented by Murray Christian and Ben Murrell in the following immunology study: Ma et al. (2021) <doi:10.1126/sciimmunol.abg6356>.

This package provides a set of functions and a class to connect, extract and upload information from the LSEG Datastream database. This package uses the DSWS API and server used by the Datastream DFO addin'. Details of this API are available at <https://www.lseg.com/en/data-analytics>. Please report issues at <https://github.com/CharlesCara/DatastreamDSWS2R/issues>.

Calculates landscape metrics for categorical landscape patterns in a tidy workflow. landscapemetrics reimplements the most common metrics from FRAGSTATS (<https://www.fragstats.org/>) and new ones from the current literature on landscape metrics. This package supports terra SpatRaster objects as input arguments. It further provides utility functions to visualize patches, select metrics and building blocks to develop new metrics.

This package provides a selection of tools that make it easier to place elements onto a (base R) plot exactly where you want them. It allows users to identify points and distances on a plot in terms of inches, pixels, margin lines, data units, and proportions of the plotting space, all in a manner more simple than manipulating par().

This package provides YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order. It is a derivative of Kirill Simonov’s PyYAML 3.11. It supports YAML 1.2 and has round-trip loaders and dumpers. It supports comments. Block style and key ordering are kept, so you can diff the source.

This package provides YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order. It is a derivative of Kirill Simonov’s PyYAML 3.11. It supports YAML 1.2 and has round-trip loaders and dumpers. It supports comments. Block style and key ordering are kept, so you can diff the source.

Brings a set of tools to help and automatically realise the description of principal component analyses (from FactoMineR functions). Detection of existing outliers, identification of the informative components, graphical views and dimensions description are performed threw dedicated functions. The Investigate() function performs all these functions in one, and returns the result as a report document (Word, PDF or HTML).

Assorted files generated from droplet-based single-cell protocols, to be used for testing functions in DropletUtils. Primarily intended for storing files that directly come out of processing pipelines like 10X Genomics CellRanger software, prior to the formation of a SingleCellExperiment object. Unlike other packages, this is not designed to provide objects that are immediately ready for analysis.

Make acoustic cues to use with the R package ndl. The package implements functions used in the PLoS ONE paper "Words from spontaneous conversational speech can be recognized with human-like accuracy by an error-driven learning algorithm that discriminates between meanings straight from smart acoustic features, bypassing the phoneme as recognition unit." doi:10.1371/journal.pone.0174623

Set of tools to simplify application of atomic forecast verification metrics for (comparative) verification of ensemble forecasts to large data sets. The forecast metrics are imported from the SpecsVerification package, and additional forecast metrics are provided with this package. Alternatively, new user-defined forecast scores can be implemented using the example scores provided and applied using the functionality of this package.