Adds standardized regression coefficients to objects created by lm'. Also extends the S3 methods print', summary and coef with additional boolean argument standardized and provides xtable'-support.

Implementations of Hurst exponent estimators based on the relationship between wavelet lifting scales and wavelet energy of Knight et al (2017) <doi:10.1007/s11222-016-9698-2>.

Fit (by Maximum Likelihood or MCMC/Bayesian), simulate, and forecast various Markov-Switching GARCH models as described in Ardia et al. (2019) <doi:10.18637/jss.v091.i04>.

Applying the methodology from Manuel et al. to estimate parameters using a matched case control data with a mismeasured exposure variable that is accompanied by instrumental variables (Submitted).

Defines classes and methods to learn models and use them to predict binary outcomes. These are generic tools, but we also include specific examples for many common classifiers.

Allow to run pylint on Python files with a R command or a RStudio addin. The report appears in the RStudio viewer pane as a formatted HTML file.

Efficient algorithm for estimating piecewise exponential hazard models for right-censored data, and is useful for reliable power calculation, study design, and event/timeline prediction for study monitoring.

This package provides functionality for the prior and posterior projected Polya tree for the analysis of circular data (Nieto-Barajas and Nunez-Antonio (2019) <arXiv:1902.06020>).

This package contains all phrasal verbs listed in <https://www.englishclub.com/ref/Phrasal_Verbs/> as data frame. Useful for educational purpose as well as for text mining.

This package provides a set of tools to extract bibliographic content from PubMed database using NCBI REST API <https://www.ncbi.nlm.nih.gov/home/develop/api/>.

Selects invalid instruments amongst a candidate of potentially bad instruments. The algorithm selects potentially invalid instruments and provides an estimate of the causal effect between exposure and outcome.

Format a number (or a list of numbers) to a string (or a list of strings) with SI prefix. Use SI prefixes as constants like (4 * milli)^2.

This package provides wrappers for scclust', a C library for computationally efficient size-constrained clustering with near-optimal performance. See <https://github.com/fsavje/scclust> for more information.

Set of tools aimed at wrapping some of the functionalities of the packages tools, utils and codetools into a nicer format so that an IDE can use them.

Fetch data on targeted public investments from Plataforma +Brasil (SICONV) <http://plataformamaisbrasil.gov.br/>, the responsible system for requests, execution, and monitoring of federal discretionary transfers in Brazil.

Accesses raw data via API and calculates social determinants of health measures for user-specified locations in the US, returning them in tidyverse- and sf-compatible data frames.

sqliter helps users, mainly data munging practioneers, to organize their sql calls in a clean structure. It simplifies the process of extracting and transforming data into useful formats.

This package contains real images of the same textile material with/without local defects, which were used in Bui and Apley (2018) <doi:10.1080/00401706.2017.1302362>.

Tidy standardized mean differences ('SMDs'). tidysmd uses the smd package to calculate standardized mean differences for variables in a data frame, returning the results in a tidy format.

An extension to the R tidy data environment for automated machine learning. The package allows fitting and cross validation of linear regression and classification algorithms on grouped data.

Helper and Wrapper functions for making shiny dashboards more easily. Functions are made modular and lower level functions are exported as well, so many use-cases are supported.

Identifies the optimal confidence level to represent the results of a set of pairwise tests as suggested by Armstrong and Poirier (2025) <doi:10.1017/pan.2024.24>.

Assesses evidence for Zipf's Law of Abbreviation in animal vocalisation using IDs, note class and note duration. The package also provides a web plot function for visualisation.

Feature-based variance-sensitive clustering of omics data. Optimizes cluster assignment by taking into account individual feature variance. Includes several modules for statistical testing, clustering and enrichment analysis.