The caRamel optimizer has been developed to meet the requirement for an automatic calibration procedure that delivers a family of parameter sets that are optimal with regard to a multi-objective target (Monteil et al. <doi:10.5194/hess-24-3189-2020>).

This package provides functions for estimating Gaussian dispersion regression models (Aitkin, 1987 <doi:10.2307/2347792>), overdispersed binomial logit models (Williams, 1987 <doi:10.2307/2347977>), and overdispersed Poisson log-linear models (Breslow, 1984 <doi:10.2307/2347661>), using a quasi-likelihood approach.

This package provides 2D and 3D tour animations as HTML widgets. The user can interact with the widgets using orbit controls, tooltips, brushing, and timeline controls. Linked brushing is supported using crosstalk', and widgets can be embedded in Shiny apps or HTML documents.

Use R to interface with the ETRADE API <https://developer.etrade.com/home>. Functions include authentication, trading, quote requests, account information, and option chains. A user will need an ETRADE brokerage account and ETRADE API approval. See README for authentication process and examples.

Data published by the United States Federal Energy Regulatory Commission including electric company financial data, natural gas company financial data, hydropower plant data, liquified natural gas plant data, oil company financial data natural gas company financial data, and natural gas storage field data.

R version of G-Series', Statistics Canada's generalized system devoted to the benchmarking and reconciliation of time series data. The methods used in G-Series essentially come from Dagum, E. B., and P. Cholette (2006) <doi:10.1007/0-387-35439-5>.

This package provides tools for estimating sample sizes primarily based on heritability, while also considering additional parameters such as statistical power and fold change. The package normalizes heritability values according to trait-specific heritability and classification to enhance accuracy in sample size estimation.

Generates HIDECAN plots that summarise and combine the results of genome-wide association studies (GWAS) and transcriptomics differential expression analyses (DE), along with manually curated candidate genes of interest. The HIDECAN plot is presented in Angelin-Bonnet et al. (2023) (currently in review).

ISA is a metadata framework to manage an increasingly diverse set of life science, environmental and biomedical experiments. In isatabr methods for reading, modifying and writing of files in the ISA-Tab format are implemented. It also contains methods for processing assay data.

Allows access to data from the Rio de Janeiro Public Security Institute (ISP), such as criminal statistics, data on gun seizures and femicide. The package also contains the spatial data of Pacifying Police Units (UPPs) and Integrated Public Safety Regions, Areas and Circumscriptions.

Multi-step adaptive elastic-net (MSAENet) algorithm for feature selection in high-dimensional regressions proposed in Xiao and Xu (2015) <DOI:10.1080/00949655.2015.1016944>, with support for multi-step adaptive MCP-net (MSAMNet) and multi-step adaptive SCAD-net (MSASNet) methods.

This package provides tools for animal movement modelling using hidden Markov models. These include processing of tracking data, fitting hidden Markov models to movement data, visualization of data and fitted model, decoding of the state process, etc. <doi:10.1111/2041-210X.12578>.

This package performs treatment allocation in two-arm clinical trials by the maximal procedure described by Berger et al. (2003) <doi:10.1002/sim.1538>. To that end, the algorithm provided by Salama et al. (2008) <doi:10.1002/sim.3014> is implemented.

This package provides a collection of functions to connect to a Moodle database, cache relevant tables locally and generate learning analytics. Moodle is an open source Learning Management System (LMS) developed by MoodleHQ. For more information about Moodle, visit <https://moodle.org>.

An interface to easily run local language models with Ollama <https://ollama.com> server and API endpoints (see <https://github.com/ollama/ollama/blob/main/docs/api.md> for details). It lets you run open-source large language models locally on your machine.

Makes output files from select PreSens Fiber Optic Oxygen Transmitters easier to work with in R. See <http://www.presens.de> for more information about PreSens (Precision Sensing GmbH). Note: this package is neither created nor maintained by PreSens.

Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahuan desert. The raw data files can be found at <https://github.com/weecology/portaldata>.

This package provides a set of datasets and functions used in the book Modele liniowe i mieszane w R, wraz z przykladami w analizie danych'. Datasets either come from real studies or are created to be as similar as possible to real studies.

Generates simple and beautiful one-page HTML reference manuals with package documentation. Math rendering and syntax highlighting are done server-side in R such that no JavaScript libraries are needed in the browser, which makes the documentation portable and fast to load.

Estimation of an S-shaped function and its corresponding inflection point via a least squares approach. A sequential mixed primal-dual based algorithm is implemented for the fast computation. Details can be found in Feng et al. (2022) <doi:10.1111/rssb.12481>.

This package provides a sparklyr extension package providing an integration with Google BigQuery'. It supports direct import/export where records are directly streamed from/to BigQuery'. In addition, data may be imported/exported via intermediate data extracts on Google Cloud Storage'.

Chooses subgroup specific optimal doses in a phase I dose finding clinical trial allowing for subgroup combination and simulates clinical trials under the subgroup specific time to event continual reassessment method. Chapple, A.G., Thall, P.F. (2018) <doi:10.1002/pst.1891>.

Extends invariant causal prediction (Peters et al., 2016, <doi:10.1111/rssb.12167>) to generalized linear and transformation models (Hothorn et al., 2018, <doi:10.1111/sjos.12291>). The methodology is described in Kook et al. (2023, <doi:10.1080/01621459.2024.2395588>).

Generate tables, listings, and graphs (TLG) using tidyverse. Tables can be created functionally, using a standard TLG process, or by specifying table and column metadata to create generic analysis summaries. The envsetup package can also be leveraged to create environments for table creation.