Lets you temporarily execute an expression or a local block with a different here() root in the here package. This is useful for sourcing code in other projects which expect the root directory of here() to be the project directory of those projects. This may be the case with git submodules for example.

This package provides a wrapper around Michel Scheffers's libassp (<https://libassp.sourceforge.net/>). The libassp (Advanced Speech Signal Processor) library aims at providing functionality for handling speech signal files in most common audio formats and for performing analyses common in phonetic science/speech science. This includes the calculation of formants, fundamental frequency, root mean square, auto correlation, a variety of spectral analyses, zero crossing rate, filtering etc. This wrapper provides R with a large subset of libassp's signal processing functions and provides them to the user in a (hopefully) user-friendly manner.

This package provides functions for computing moments and coefficients related to the Beta-Wishart and Inverse Beta-Wishart distributions. It includes functions for calculating the expectation of matrix-valued functions of the Beta-Wishart distribution, coefficient matrices C_k and H_k, expectation of matrix-valued functions of the inverse Beta-Wishart distribution, and coefficient matrices \tildeC_k and \tildeH_k. For more details, refer Hillier and Kan (2024) <https://www-2.rotman.utoronto.ca/~kan/papers/wishmom.pdf>, "On the Expectations of Equivariant Matrix-valued Functions of Wishart and Inverse Wishart Matrices".

Read from, interogate, and write to Wikidata <https://www.wikidata.org> - the multilingual, interdisciplinary, semantic knowledgebase. Includes functions to: read from wikidata (single items, properties, or properties); query wikidata (retrieving all items that match a set of criterial via Wikidata SPARQL query service); write to Wikidata (adding new items or statements via QuickStatements); and handle and manipulate Wikidata objects (as lists and tibbles). Uses the Wikidata and Quickstatements APIs.

This package provides a comprehensive data analysis framework for NIH-funded research that streamlines workflows for both data cleaning and preparing NIH Data Archive ('NDA') submission templates. Provides unified access to multiple data sources ('REDCap', MongoDB', Qualtrics') through interfaces to their APIs, with specialized functions for data cleaning, filtering, merging, and parsing. Features automatic validation, field harmonization, and memory-aware processing to enhance reproducibility in multi-site collaborative research as described in Mittal et al. (2021) <doi:10.20900/jpbs.20210011>.

Fits the combination of Wavelet-GARCH model for time series forecasting using algorithm by Paul (2015) <doi:10.3233/MAS-150328>.

This package provides a Stata-style `webuse()` function for importing named datasets from Stata's online collection.

Support for interfaces from R to other languages, built around a class for evaluators and a combination of functions, classes and methods for communication. Will be used through a specific language interface package. Described in the book "Extending R".

XML package for creating and reading and manipulating XML', with an object model based on Reference Classes'.

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.

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>.

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.

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>.

Adding some at-present missing functionality, or functions unlikely to be added to the base xpose package. This includes some diagnostic plots that have been missing in translation from xpose4', but also some useful features that truly extend the capabilities of what can be done with xpose'. These extensions include the concept of a set of xpose objects, and diagnostics for likelihood-based models.

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.

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.

This collection of gene representation-independent mechanisms for evolutionary and genetic algorithms contains four groups of functions: First, functions for selecting a gene in a population of genes according to its fitness value and for adaptive scaling of the fitness values as well as for performance optimization and measurement offer several variants for implementing the survival of the fittest. Second, evaluation functions for deterministic functions avoid recomputation. Evaluation of stochastic functions incrementally improve the estimation of the mean and variance of fitness values at almost no additional cost. Evaluation functions for gene repair handle error-correcting decoders. Third, timing and counting functions for profiling the algorithm pipeline are provided to assess bottlenecks in the algorithms. Fourth, a small collection of problem environments for function optimization, combinatorial optimization, and grammar-based genetic programming and grammatical evolution is provided for tutorial examples. The methods in the package are described by the following references: Baker, James E. (1987, ISBN:978-08058-0158-8), De Jong, Kenneth A. (1975) <https://deepblue.lib.umich.edu/handle/2027.42/4507>, Geyer-Schulz, Andreas (1997, ISBN:978-3-7908-0830-X), Grefenstette, John J. (1987, ISBN:978-08058-0158-8), Grefenstette, John J. and Baker, James E. (1989, ISBN:1-55860-066-3), Holland, John (1975, ISBN:0-472-08460-7), Lau, H. T. (1986) <doi:10.1007/978-3-642-61649-5>, Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005) <doi:10.1007/3-540-31306-0>, Reynolds, J. C. (1993) <doi:10.1007/BF01019459>, Schaffer, J. David (1989, ISBN:1-55860-066-3), Wenstop, Fred (1980) <doi:10.1016/0165-0114(80)90031-7>, Whitley, Darrell (1989, ISBN:1-55860-066-3), Wickham, Hadley (2019, ISBN:978-815384571).

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>.

Extremely fast hashing of R objects using xxHash'. R objects are hashed via the standard serialization mechanism in R. Raw byte vectors and strings can be handled directly for compatibility with hashes created on other systems. This implementation is a wrapper around the xxHash C library which is available from <https://github.com/Cyan4973/xxHash>.

This package provides a few functions which provide a quick way of subsetting genomic admixture data and generating customizable stacked barplots.

Provide R functions to read/write/format Excel 2007 and Excel 97/2000/XP/2003 file formats.

Based on STATA xtsum command, it is used to compute summary statistics for a panel data set. It generates overall, between-group, and within-group statistics for specified variables in a panel data set, as presented in S. Porter (2023) <https://stephenporter.org/files/xtsum_handout.pdf>, StataCorp (2023) <https://www.stata.com/manuals/xtxtsum.pdf>.

An extension for the xml2 package to transform XML documents by applying an xslt style-sheet.

Institutional performance assessment remains a key challenge to a multitude of stakeholders. Existing indicators such as h-type indicators, g-type indicators, and many others do not reflect expertise of institutions that defines their research portfolio. The package offers functionality to compute and visualise two novel indices: the x-index and the xd-index. The x-index evaluates an institution's scholarly expertise within a specific discipline or field, while the xd-index provides a broader assessment of overall scholarly expertise considering an institution's publication pattern and strengths across coarse thematic areas. These indices offer a nuanced understanding of institutional research capabilities, aiding stakeholders in research management and resource allocation decisions. Lathabai, H.H., Nandy, A., and Singh, V.K. (2021) <doi:10.1007/s11192-021-04188-3>. Nandy, A., Lathabai, H.H., and Singh, V.K. (2023) <doi:10.5281/zenodo.8305585>. This package provides the h-, g-, x-, xd-indices, and their variants for use with standard format of Web of Science (WoS) scrapped datasets.