This package provides typed parameter documentation tags for integration with roxygen2'. Typed parameter tags provide a consistent interface for annotating expected types for parameters and returned values. Tools for converting from existing styles are also provided to easily adapt projects which implement typed documentation by convention rather than tag. Use the default format or provide your own.

Circular / ring buffers in R and C. There are a couple of different buffers here with different implementations that represent different trade-offs.

Robust Estimation of Variance Component Models by classic and composite robust procedures. The composite procedures are robust against outliers generated by the Independent Contamination Model.

Electrical properties of resistor networks using matrix methods.

Interface to the Dryad "Solr" API, their "OAI-PMH" service, and fetch datasets. Dryad (<https://datadryad.org/>) is a curated host of data underlying scientific publications.

Generates random walks of various types by providing a set of functions that are compatible with the tidyverse'. The functions provided in the package make it simple to create random walks with a variety of properties, such as how many simulations to run, how many steps to take, and the distribution of random walk itself.

Protocol Buffers are a way of encoding structured data in an efficient yet extensible format. Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. Additional documentation is available in two included vignettes one of which corresponds to our JSS paper (2016, <doi:10.18637/jss.v071.i02>. A sufficiently recent version of Protocol Buffers library is required; currently version 3.3.0 from 2017 is the stated minimum.

MsgPack header files are provided for use by R packages, along with the ability to access, create and alter MsgPack objects directly from R. MsgPack is an efficient binary serialization format. It lets you exchange data among multiple languages like JSON but it is faster and smaller. Small integers are encoded into a single byte, and typical short strings require only one extra byte in addition to the strings themselves. This package provides headers from the msgpack-c implementation for C and C++(11) for use by R, particularly Rcpp'. The included msgpack-c headers are licensed under the Boost Software License (Version 1.0); the code added by this package as well the R integration are licensed under the GPL (>= 2). See the files COPYRIGHTS and AUTHORS for a full list of copyright holders and contributors to msgpack-c'.

BM25 is a ranking function used by search engines to rank matching documents according to their relevance to a user's search query. This package provides a light wrapper around the BM25 rust crate for Okapi BM25 text search. For more information, see Robertson et al. (1994) <https://trec.nist.gov/pubs/trec3/t3_proceedings.html>.

Assists in the whole process of designing and evaluating Randomized Control Trials. Robust treatment assignment by strata/blocks, that handles misfits; Power calculations of the minimum detectable treatment effect or minimum populations; Balance tables of T-test of covariates; Balance Regression: (treatment ~ all x variables) with F-test of null model; Impact_evaluation: Impact evaluation regressions. This function gives you the option to include control_vars, fixed effect variables, cluster variables (for robust SE), multiple endogenous variables and multiple heterogeneous variables (to test treatment effect heterogeneity) summary_statistics: Function that creates a summary statistics table with statistics rank observations in n groups: Creates a factor variable with n groups. Each group has a min and max label attach to each category. Athey, Susan, and Guido W. Imbens (2017) <arXiv:1607.00698>.

This package provides a framework that supports creating and extending enterprise Shiny applications using best practices.

The handling of an API key (misnomer for password) for protected data can be difficult. This package provides secure convenience functions for entering / handling API keys and pulling data directly into memory. By default it will load from REDCap instances, but other sources are injectable via inversion of control.

This package provides a collection of functions to simulate luminescence signals in quartz and Al2O3 based on published models.

Polynomially bounded algorithms to aggregate complete rankings under Kemeny's axiomatic framework. RankAggSIgFUR (pronounced as rank-agg-cipher) contains two heuristics algorithms: FUR and SIgFUR. For details, please see Badal and Das (2018) <doi:10.1016/j.cor.2018.06.007>.

Allows interaction with Interactive Brokers Trader Workstation <https://interactivebrokers.github.io/tws-api/>. Handles the connection over the network and the exchange of messages. Data is encoded and decoded between user and wire formats. Data structures and functionality closely mirror the official implementations.

This package provides a set of R functions to output Rich Text Format (RTF) files with high resolution tables and graphics that may be edited with a standard word processor such as Microsoft Word.

External jars required for package RMOA. RMOA is a framework to build data stream models on top of MOA (Massive Online Analysis - <https://moa.cms.waikato.ac.nz/>). The jar files are put in this R package, the modelling logic can be found in the RMOA package.

This package provides a compact R interface for performing tensor calculations. This is achieved by allowing (upper and lower) index labeling of arrays and making use of Ricci calculus conventions to implicitly trigger contractions and diagonal subsetting. Explicit tensor operations, such as addition, subtraction and multiplication of tensors via the standard operators, raising and lowering indices, taking symmetric or antisymmetric tensor parts, as well as the Kronecker product are available. Common tensors like the Kronecker delta, Levi Civita epsilon, certain metric tensors, the Christoffel symbols, the Riemann as well as Ricci tensors are provided. The covariant derivative of tensor fields with respect to any metric tensor can be evaluated. An effort was made to provide the user with useful error messages.

This package provides a solution path for Reinforced Angle-based Multicategory Support Vector Machines, with linear learning, polynomial learning, and Gaussian kernel learning. C. Zhang, Y. Liu, J. Wang and H. Zhu. (2016) <doi:10.1080/10618600.2015.1043010>.

This package provides functions for phylogenetic analysis (Castiglione et al., 2018 <doi:10.1111/2041-210X.12954>). The functions perform the estimation of phenotypic evolutionary rates, identification of phenotypic evolutionary rate shifts, quantification of direction and size of evolutionary change in multivariate traits, the computation of ontogenetic shape vectors and test for morphological convergence.

Calculate the matrices in Shiller (1991, <doi:10.1016/S1051-1377(05)80028-2>) that serve as the foundation for many repeat-sales price indexes.

This package provides a comprehensive set of regular expression functions based on those found in Python without relying on reticulate'. It provides functions that intend to (1) make it easier for users familiar with Python to work with regular expressions, (2) reduce the complexity often associated with regular expressions code, (3) and enable users to write more readable and maintainable code that relies on regular expression-based pattern matching.

Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).

Listings are often part of the submission of clinical trial data in regulatory settings. We provide a framework for the specific formatting features often used when displaying large datasets in that context.