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This package provides comprehensive functionality to read, write and format Excel data.
XML package for creating and reading and manipulating XML', with an object model based on Reference Classes'.
Create beautifully color-coordinated and customized themes for your xaringan slides, without writing any CSS. Complete your slide theme with ggplot2 themes that match the font and colors used in your slides. Customized styles can be created directly in your slides R Markdown source file or in a separate external script.
This package implements an iterative mean-variance panel regression estimator that allows both the mean and variance of the dependent variable to be functions of covariates. The method alternates between estimating a mean equation (using generalized linear models with Gaussian family) and a variance equation (using generalized linear models with Gamma family on squared within-group residuals) until convergence. Based on the methodology in Mooi-Reci and Liao (2025) <doi:10.1093/esr/jcae052>.
An R interface to the OpenPyXL Python library to create native Excel charts and work with Microsoft Excel files.
An implementation of the RuleFit algorithm as described in Friedman & Popescu (2008) <doi:10.1214/07-AOAS148>. eXtreme Gradient Boosting ('XGBoost') is used to build rules, and glmnet is used to fit a sparse linear model on the raw and rule features. The result is a model that learns similarly to a tree ensemble, while often offering improved interpretability and achieving improved scoring runtime in live applications. Several algorithms for reducing rule complexity are provided, most notably hyperrectangle de-overlapping. All algorithms scale to several million rows and support sparse representations to handle tens of thousands of dimensions.
Miscellaneous functions used for x-engineering (feature engineering) or for supporting in other packages maintained by Shichen Xie'.
This package provides tools to build CDISC compliant data sets and check for CDISC compliance.
Download data from individual XKCD comics, written by Randall Munroe <https://xkcd.com/>.
Extrema-weighted feature extraction for varying length functional data. Functional data analysis method that performs dimensionality reduction based on predefined features and allows for quantile weighting. Method implemented as presented in van den Boom et al. (2018) <doi:10.1093/bioinformatics/bty120>.
Supports a structured approach for exploring PKPD data <https://opensource.nibr.com/xgx/>. It also contains helper functions for enabling the modeler to follow best R practices (by appending the program name, figure name location, and draft status to each plot). In addition, it enables the modeler to follow best graphical practices (by providing a theme that reduces chart ink, and by providing time-scale, log-scale, and reverse-log-transform-scale functions for more readable axes). Finally, it provides some data checking and summarizing functions for rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets.
Converts an XLSForm (survey in Excel') into a well-structured Word document, including sections, skip logic, options, and question labels. Designed to support survey documentation, training materials, and data collection workflows. The package was developed based on field experience with XLSForm and humanitarian operations, aiming to streamline documentation and enhance training efficiency.
The circadian period of a time series data is predicted and the statistical significance of the periodicity are calculated using the chi-square periodogram.
This package provides a set of functions devoted to multivariate exploratory statistics on textual data. Classical methods such as correspondence analysis and agglomerative hierarchical clustering are available. Chronologically constrained agglomerative hierarchical clustering enriched with labelled-by-words trees is offered. Given a division of the corpus into parts, their characteristic words and documents are identified. Further, accessing to FactoMineR functions is very easy. Two of them are relevant in textual domain. MFA() addresses multiple lexical table allowing applications such as dealing with multilingual corpora as well as simultaneously analyzing both open-ended and closed questions in surveys. See <http://xplortext.unileon.es> for examples.
Analysis of crossover interference in experimental crosses, particularly regarding the gamma model. See, for example, Broman and Weber (2000) <doi:10.1086/302923>.
High-level functions to render LaTeX fragments in plots, including as labels and data symbols in ggplot2 plots, plus low-level functions to author LaTeX fragments (to produce LaTeX documents), typeset LaTeX documents (to produce DVI files), read DVI files (to produce "DVI" objects), and render "DVI" objects.
There are two new network metrics, RWC (random walk centrality) and CBET (counting betweenness). Also available are the normalized versions of those metrics. These measures of centrality and betweenness are particularly useful for the analysis of very dense weighted networks which include loops. Traditional measures do not work as well for those network characteristics. The main reference is DePaolis at al (2022) <doi:10.1007/s41109-022-00519-2>.
Converts XML documents to R dataframes and dataframes to XML documents. A wide variety of options allows for different XML formats and flexible control of the conversion process. Results can be exported to CSV and Excel, if desired. Also converts XML data to R lists.
There is limited native support for external pointers in the R interface. This package provides some basic tools to verify, create and modify externalptr objects.
Helpers for transforming XML content into number of tables while preserving parent to child relationships.
The x3p file format is specified in ISO standard 5436:2000 to describe 3d surface measurements. x3ptools allows reading, writing and basic modifications to the 3D surface measurements.
Computes robust association measures that do not presuppose linearity. The xi correlation (xicor) is based on cross correlation between ranked increments. The reference for the methods implemented here is Chatterjee, Sourav (2020) <arXiv:1909.10140> This package includes the Galton peas example.
This package implements a probabilistic approach to time series forecasting combining XGBoost regression with conformal inference methods. The package provides functionality for generating predictive distributions, evaluating uncertainty, and optimizing hyperparameters using Bayesian, coarse-to-fine, or random search strategies.
The XKCD color survey asked participants to name colours. Randall Munroe published the top thousand(roughly) names and their sRGB hex values. This package lets you use them.