This package provides a native R implementation for encoding and decoding sixel graphics (<https://vt100.net/docs/vt3xx-gp/chapter14.html>), and a dedicated sixel graphics device that allows plots to be rendered directly within compatible terminal emulators.

Computes linear Bayesian spectral estimates from multirate data for second-order stationary time series. Provides credible intervals and methods for plotting various spectral estimates. Please see the paper `Should we sample a time series more frequently? (doi below) for a full description of and motivation for the methodology.

This package implements random variables by means of S4 classes and methods.

This package provides a collection of functions to compute the Rao-Stirling diversity index (Porter and Rafols, 2009) <DOI:10.1007/s11192-008-2197-2> and its extension to acknowledge missing data (i.e., uncategorized references) by calculating its interval of uncertainty using mathematical optimization as proposed in Calatrava et al. (2016) <DOI:10.1007/s11192-016-1842-4>. The Rao-Stirling diversity index is a well-established bibliometric indicator to measure the interdisciplinarity of scientific publications. Apart from the obligatory dataset of publications with their respective references and a taxonomy of disciplines that categorizes references as well as a measure of similarity between the disciplines, the Rao-Stirling diversity index requires a complete categorization of all references of a publication into disciplines. Thus, it fails for a incomplete categorization; in this case, the robust extension has to be used, which encodes the uncertainty caused by missing bibliographic data as an uncertainty interval. Classification / ACM - 2012: Information systems ~ Similarity measures, Theory of computation ~ Quadratic programming, Applied computing ~ Digital libraries and archives.

Client for ChromaDB', a vector database for storing and querying embeddings. This package provides a convenient interface to interact with the REST API of ChromaDB <https://docs.trychroma.com>.

Fits non-linear regression models on dependant data with Generalised Least Square (GLS) based Random Forest (RF-GLS) detailed in Saha, Basu and Datta (2021) <doi:10.1080/01621459.2021.1950003>.

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 RDF storage and SPARQL 1.1 query capabilities by wrapping the Oxigraph graph database library <https://github.com/oxigraph/oxigraph>. Supports in-memory and persistent ('RocksDB') storage, multiple RDF serialization formats ('Turtle', N-Triples', RDF-XML', N-Quads', TriG'), and full SPARQL 1.1 Query and Update support. Built using the extendr framework for Rust'-R bindings.

Fit and deploy rotation forest models ("Rodriguez, J.J., Kuncheva, L.I., 2006. Rotation forest: A new classifier ensemble method. IEEE Trans. Pattern Anal. Mach. Intell. 28, 1619-1630 <doi:10.1109/TPAMI.2006.211>") for binary classification. Rotation forest is an ensemble method where each base classifier (tree) is fit on the principal components of the variables of random partitions of the feature set.

An enhanced version of the semi-empirical, spatially distributed emission and transport model PhosFate implemented in R and C++'. It is based on the D-infinity, but also supports the D8 flow method. The currently available substances are suspended solids (SS) and particulate phosphorus (PP). A major feature is the allocation of substance loads entering surface waters to their sources of origin, which is a basic requirement for the identification of critical source areas and in consequence a cost-effective implementation of mitigation measures. References: Hepp et al. (2022) <doi:10.1016/j.jenvman.2022.114514>; Hepp and Zessner (2019) <doi:10.3390/w11102161>; Kovacs (2013) <http://hdl.handle.net/20.500.12708/9468>.

An R implementation of the Reinert text clustering method. For more details about the algorithm see the included vignettes or Reinert (1990) <doi:10.1177/075910639002600103>.

An approach to age-depth modelling that uses Bayesian statistics to reconstruct accumulation histories for deposits, through combining radiocarbon and other dates with prior information on accumulation rates and their variability. See Blaauw & Christen (2011).

This package provides a tool for mass deployment of shiny apps to RStudio Connect or Shiny Server'. Multiple user accounts and servers can be configured for deployment.

Estimates life tables, specifically (crude) death rates and (raw and graduated) death probabilities, using rolling windows in one (e.g., age), two (e.g., age and time) or three (e.g., age, time and income) dimensions. The package can also be utilised for summarising statistics and smoothing continuous variables through rolling windows in other domains, such as estimating averages of self-positioning ideology in political science. Acknowledgements: The authors wish to thank Ministerio de Ciencia, Innovación y Universidades (grant PID2021-128228NB-I00) and Generalitat Valenciana (grants HIECPU/2023/2, Conselleria de Hacienda, Economà a y Administración Pública, and CIGE/2023/7, Conselleria de Educación, Cultura, Universidades y Empleo) for supporting this research.

Set of utilities to facilitate the reproduction of analysis in R. It allow to make_structure(), clean_structure(), and run and log programs in a predefined order to allow secondary files, analysis and reports be constructed in an ordered and reproducible form.

CausalEGM is a general causal inference framework for estimating causal effects by encoding generative modeling, which can be applied in both discrete and continuous treatment settings. A description of the methods is given in Liu (2022) <arXiv:2212.05925>.

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. The rdmulti package provides tools to analyze RD designs with multiple cutoffs or scores: rdmc() estimates pooled and cutoff specific effects for multi-cutoff designs, rdmcplot() draws RD plots for multi-cutoff designs and rdms() estimates effects in cumulative cutoffs or multi-score designs. See Cattaneo, Titiunik and Vazquez-Bare (2020) <https://rdpackages.github.io/references/Cattaneo-Titiunik-VazquezBare_2020_Stata.pdf> for further methodological details.

The mixed integer programming library MIPLIB (see <http://miplib.zib.de/>) is commonly used to compare the performance of mixed integer optimization solvers. This package provides functions to access MIPLIB from the R Optimization Infrastructure ('ROI'). More information about MIPLIB can be found in the paper by Koch et al. available at <http://mpc.zib.de/index.php/MPC/article/viewFile/56/28>. The README.md file illustrates how to use this package.

Automated performance of common transformations used to fulfill parametric assumptions of normality and identification of the best performing method for the user. Output for various normality tests (Thode, 2002) corresponding to the best performing method and a descriptive statistical report of the input data in its original units (5-number summary and mathematical moments) are also presented. Lastly, the Rankit, an empirical normal quantile transformation (ENQT) (Soloman & Sawilowsky, 2009), is provided to accommodate non-standard use cases and facilitate adoption. <DOI: 10.1201/9780203910894>. <DOI: 10.22237/jmasm/1257034080>.

Testing and inference for regression models using residual randomization methods. The basis of inference is an invariance assumption on the regression errors, e.g., clustered errors, or doubly-clustered errors.

The Rearrangement Correlation Coefficient is an adjusted version of Pearson's correlation coefficient that accurately measures monotonic dependence relationships, including both linear and nonlinear associations. This method addresses the underestimation problem of classical correlation coefficients in nonlinear monotonic scenarios through improved statistical bounds derived from rearrangement inequalities. For more details, see Ai (2024) <doi:10.52202/079017-1180>.

This holds r markdown and quarto templates for academic papers and slide decks. It also has templates to create research projects which contain academic papers as vignettes.

This package provides a collection of randomization tests, data sets and examples. The current version focuses on five testing problems and their implementation in empirical work. First, it facilitates the empirical researcher to test for particular hypotheses, such as comparisons of means, medians, and variances from k populations using robust permutation tests, which asymptotic validity holds under very weak assumptions, while retaining the exact rejection probability in finite samples when the underlying distributions are identical. Second, the description and implementation of a permutation test for testing the continuity assumption of the baseline covariates in the sharp regression discontinuity design (RDD) as in Canay and Kamat (2018) <https://goo.gl/UZFqt7>. More specifically, it allows the user to select a set of covariates and test the aforementioned hypothesis using a permutation test based on the Cramer-von Misses test statistic. Graphical inspection of the empirical CDF and histograms for the variables of interest is also supported in the package. Third, it provides the practitioner with an effortless implementation of a permutation test based on the martingale decomposition of the empirical process for testing for heterogeneous treatment effects in the presence of an estimated nuisance parameter as in Chung and Olivares (2021) <doi:10.1016/j.jeconom.2020.09.015>. Fourth, this version considers the two-sample goodness-of-fit testing problem under covariate adaptive randomization and implements a permutation test based on a prepivoted Kolmogorov-Smirnov test statistic. Lastly, it implements an asymptotically valid permutation test based on the quantile process for the hypothesis of constant quantile treatment effects in the presence of an estimated nuisance parameter.

The R Analytic Tool To Learn Easily (Rattle) provides a collection of utilities functions for the data scientist. This package (v5.6.0) supports the companion graphical interface with the aim to provide a simple and intuitive introduction to R for data science, allowing a user to quickly load data from a CSV file transform and explore the data, and to build and evaluate models. A key aspect of the GUI is that all R commands are logged and commented through the log tab. This can be saved as a standalone R script file and as an aid for the user to learn R or to copy-and-paste directly into R itself. If you want to use the older Rattle implementing the GUI in RGtk2 (which is no longer available from CRAN) then please install the Rattle package v5.5.1. See rattle.togaware.com for instructions on installing the modern Rattle graphical user interface.