R interface to access prices and market data with the Bloomberg Data License service from <https://www.bloomberg.com/professional/product/data-license/>. As a prerequisite, a valid Data License from Bloomberg is needed together with the corresponding SFTP credentials and whitelisting of the IP from which accessing the service. This software and its author are in no way affiliated, endorsed, or approved by Bloomberg or any of its affiliates. Bloomberg is a registered trademark.

PandocRuby is a wrapper for Pandoc, a Haskell library with command line tools for converting one markup format to another. Pandoc can convert documents from a variety of formats including markdown, reStructuredText, textile, HTML, DocBook, LaTeX, and MediaWiki markup to a variety of other formats, including markdown, reStructuredText, HTML, LaTeX, ConTeXt, PDF, RTF, DocBook XML, OpenDocument XML, ODT, GNU Texinfo, MediaWiki markup, groff man pages, HTML slide shows, EPUB, Microsoft Word docx, and more.

This package provides provides a `MaybeOwned` (and `MaybeOwnedMut`) type similar to std's `Cow` but it implements `From<T>` and `From<&'a T>` and does not require `ToOwned`.

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.

Validate dataset by columns and rows using convenient predicates inspired by assertr package. Generate good looking HTML report or print console output to display in logs of your data processing pipeline.

This package provides functions for identification of putative causal loci in whole-genome sequencing data. The functions allow genome-wide association scan. It also includes an efficient knockoff generator for genetic data.

Data handling and estimation functions for animal movement estimation from archival or satellite tags. Helper functions are included for making image summaries binned by time interval from Markov Chain Monte Carlo simulations.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was Mouse430\_2\_probe\_tab.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was PrimeView\_probe\_tab.

Mass-Spectrometry based spatial proteomics have enabled the proteome-wide mapping of protein subcellular localization (Orre et al. 2019, Molecular Cell). SubCellBarCode R package robustly classifies proteins into corresponding subcellular localization.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was Sugar\_Cane\_probe\_tab.

This package stores motif collections as lists of position frequency matrix (PWMatrixList) objects provided by the TFBSTools package for use in R with packages like motifmatchr or chromVAR.

This package provides a stable implementation of the upcoming new `proc_macro` API. Comes with an option, off by default, to also reimplement itself in terms of the upstream unstable API.

This package provides a stable implementation of the upcoming new `proc_macro` API. Comes with an option, off by default, to also reimplement itself in terms of the upstream unstable API.

This package provides a novel ensemble method employing Support Vector Machines (SVMs) as base learners. This powerful ensemble model is designed for both classification (Ara A., et. al, 2021) <doi:10.6339/21-JDS1014>, and regression (Ara A., et. al, 2021) <doi:10.1016/j.eswa.2022.117107> problems, offering versatility and robust performance across different datasets and compared with other consolidated methods as Random Forests (Maia M, et. al, 2021) <doi:10.6339/21-JDS1025>.

These tools help you to assess if a corporate lending portfolio aligns with climate goals. They summarize key climate indicators attributed to the portfolio (e.g. production, emission factors), and calculate alignment targets based on climate scenarios. They implement in R the last step of the free software PACTA (Paris Agreement Capital Transition Assessment; <https://www.transitionmonitor.com/>). Financial institutions use PACTA to study how their capital allocation decisions align with climate change mitigation goals.

Facilitate Pharmacokinetic (PK) and Pharmacodynamic (PD) modeling and simulation with powerful tools for Nonlinear Mixed-Effects (NLME) modeling. The package provides access to the same advanced Maximum Likelihood algorithms used by the NLME-Engine in the Phoenix platform. These tools support a range of analyses, from parametric methods to individual and pooled data analysis <https://www.certara.com/app/uploads/2020/06/BR_PhoenixNLME-v4.pdf>. Execution is supported both locally or on remote machines.

Overrides function-key-map parent for preferred input-method to translate input sequences the default system layout (english) so we can use Emacs bindings while non-default system layout is active.

Client for AWS Comprehend <https://aws.amazon.com/comprehend>, a cloud natural language processing service that can perform a number of quantitative text analyses, including language detection, sentiment analysis, and feature extraction.

This package provides functionality for determining the sample size of replication studies using Bayesian design approaches in the normal-normal hierarchical model (Pawel et al., 2022) <doi:10.48550/arXiv.2211.02552>.

Visualization and analysis tools to aid in the interpretation of neural network models. Functions are available for plotting, quantifying variable importance, conducting a sensitivity analysis, and obtaining a simple list of model weights.

Shiny UI to identify cliques of related constructs in repertory grid data. See Burr, King, & Heckmann (2020) <doi:10.1080/14780887.2020.1794088> for a description of the interpretive clustering (IC) method.

Based on Shapley values to explain multivariate outlyingness and to detect and impute cellwise outliers. Includes implementations of methods described in Mayrhofer and Filzmoser (2023) <doi:10.1016/j.ecosta.2023.04.003>.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was E\_coli\_Asv2\_probe\_tab.