This package provides access to global river gauge data from a variety of national-level river agencies. The package interfaces with the national-level agency websites to provide access to river gauge locations, river discharge, and river stage. Currently, the package is available for the following countries: Argentina, Australia, Brazil, Canada, Chile, France, Germany, Japan, South Africa, the United Kingdom, and the United States.

The trimmed k-means clustering method by Cuesta-Albertos, Gordaliza and Matran (1997). This optimizes the k-means criterion under trimming a portion of the points.

This package contains functionality for performing the following methods of p-value aggregation: Fisher's method, the Lancaster method (weighted Fisher's method), and Sidak correction.

This package creates a lightweight way to add markdown helpfiles to Shiny apps, using modal dialog boxes, with no need to observe each help button separately.

This package provides a package to suggest the number of mutational signatures in a collection of somatic mutations using calculating the cross-validated perplexity score.

This data package contains a subset of the Bodenmiller et al, Nat Biotech 2012 dataset for testing single cell, high dimensional analysis and visualization methods.

This data package contains monthly climate data in Germany, it can be used for heating and cooling calculations (external temperature, heating / cooling days, solar radiation).

Fit a mixture of Discrete Laplace distributions using plain numerical optimisation. This package has similar applications as the disclapmix package that uses an EM algorithm.

Generates an RMarkdown data report with two components: a summary of an input dataset and a diff of the dataset relative to an old version.

Bayesian Model Averaging to create probabilistic forecasts from ensemble forecasts and weather observations <https://stat.uw.edu/sites/default/files/files/reports/2007/tr516.pdf>.

Fit and sample from the ensemble model described in Spence et al (2018): "A general framework for combining ecosystem models"<doi:10.1111/faf.12310>.

This package provides tools for analyzing remote sensing forest data, including functions for detecting treetops from canopy models, outlining tree crowns, and calculating textural metrics.

This package implements imputation methods using EM and Data Augmentation for multinomial data following the work of Schafer 1997 <ISBN: 978-0-412-04061-0>.

This package provides tools for mapping International Classification of Diseases codes to comorbidity, enabling the identification and analysis of various medical conditions within healthcare data.

Miscellaneous functions commonly used by LuLab. This package aims to help more researchers on epidemiology to perform data management and visualization more efficiently.

Give access to MUI X Tree View components, which lets users navigate hierarchical lists of data with nested levels that can be expanded and collapsed.

Bundles the datasets and functions used in the textbook by Philip Pollock and Barry Edwards, an R Companion to Essentials of Political Analysis, Second Edition.

Allows to retrieve time series of all indicators available in the Bank of Mexico's Economic Information System (<http://www.banxico.org.mx/SieInternet/>).

This package provides tools which allow regression variables to be placed on similar scales, offering computational benefits as well as easing interpretation of regression output.

Transformer is a Deep Neural Network Architecture based i.a. on the Attention mechanism (Vaswani et al. (2017) <doi:10.48550/arXiv.1706.03762>).

Calculate Expert Team on Climate Change Detection and Indices (ETCCDI) <-- (acronym) climate indices from daily or hourly temperature and precipitation data. Provides flexible data handling.

Fast computation of Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) for weighted binary classification problems (weights are example-specific cost values).

This package performs comparative bioavailability calculations for Average Bioequivalence with Expanding Limits (ABEL). Implemented are Method A / Method B and the detection of outliers. If the design allows, assessment of the empiric Type I Error and iteratively adjusting alpha to control the consumer risk. Average Bioequivalence - optionally with a tighter (narrow therapeutic index drugs) or wider acceptance range (South Africa: Cmax) - is implemented as well.

The sourcetools package provides both an R and C++ interface for the tokenization of R code, and helpers for interacting with the tokenized representation of R code.