Hyperlink Automatic Detection

Automatic detection of hyperlinks for packages and calls in the text of 'rmarkdown' or 'quarto' documents.

Analysis of Spatial Stratified Heterogeneity

Detecting spatial associations via spatial stratified heterogeneity, accounting for spatial dependencies, interpretability, complex interactions, and robust stratification. In addition, it supports the spatial stratified heterogeneity family described in Lv et al. (2025).

PharmacoVigilance Signal Detection

A collection of several pharmacovigilance signal detection methods extended to the multiple comparison setting.

Fast Change Point Detection via Sequential Gradient Descent

Implements fast change point detection algorithm based on the paper "Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis" by Xianyang Zhang, Trisha Dawn < https://proceedings.mlr.press/v206/zhang23b.html>. The algorithm is based on dynamic programming with pruning and sequential gradient descent. See Li and Zhang (2026) for details.

Backward Procedure for Change-Point Detection

Implements a backward procedure for single and multiple change point detection proposed by Shin et al. . The backward approach is particularly useful to detect short and sparse signals which is common in copy number variation (CNV) detection.

Outliers Detection

Provides functions for detecting outliers in datasets using statistical methods. The package supports identification of anomalous observations in numerical data and is intended for use in data cleaning, exploratory data analysis, and preprocessing workflows.

Multivariate Outlier Detection Methods

Provides methods for detecting multivariate outliers in numeric datasets. The package implements classical Mahalanobis distance, robust Minimum Covariance Determinant (MCD), and Principal Component Analysis (PCA)-based approaches for outlier detection. The methodology is informed by Aggarwal (2017) and Grentzelos, Caroni and Barranco-Chamorro (2020) . Visualization functions are included to aid interpretation of detected outliers. Mahalanobis distance calculations are accelerated using 'C++' through 'Rcpp'.

Detect and Treat Outliers in Data Mining

Implements a suite of tools for outlier detection and treatment in data mining. It includes univariate methods (Z-score, Interquartile Range), multivariate detection using Mahalanobis distance, and density-based detection (Local Outlier Factor) via the 'dbscan' package. It also provides functions for visualization using 'ggplot2' and data cleaning via Winsorization.

QTL Hotspot Detection

This function produces both the numerical and graphical summaries of the QTL hotspot detection in the genomes that are available on the worldwide web including the flanking markers of QTLs.

Easily Download 'EconDataverse' Datasets

The 'EconDataverse' is a universe of open-source packages to work seamlessly with economic data. This package is designed to make it easy to download selected datasets that are preprocessed by 'EconDataverse' packages and publicly hosted on 'Hugging Face'. Learn more about the 'EconDataverse' at < https://www.econdataverse.org>.