Despite the predominant use of R for data manipulation and various robust statistical calculations, in recent years, more people from various disciplines are beginning to use R for other purposes. In doing this seemlessly, further tools are needed users to easily and freely write in R for all kinds of purposes. The r2dictionary introduces a means for users to directly search for definitions of terms within the R environment.

This package provides a method generate() is implemented in this package for the random generation of vector time series according to models obtained by RMAWGEN', vars or other packages. This package was created to generalize the algorithms of the RMAWGEN package for the analysis and generation of any environmental vector time series.

This package provides functions for risk management and portfolio investment of securities with practical tools for data processing and plotting. Moreover, it contains functions which perform the COS Method, an option pricing method based on the Fourier-cosine series (Fang, F. (2008) <doi:10.1137/080718061>).

Creation, estimation, and prediction of random weight neural networks (RWNN), Schmidt et al. (1992) <doi:10.1109/ICPR.1992.201708>, including popular variants like extreme learning machines, Huang et al. (2006) <doi:10.1016/j.neucom.2005.12.126>, sparse RWNN, Zhang et al. (2019) <doi:10.1016/j.neunet.2019.01.007>, and deep RWNN, Henrà quez et al. (2018) <doi:10.1109/IJCNN.2018.8489703>. It further allows for the creation of ensemble RWNNs like bagging RWNN, Sui et al. (2021) <doi:10.1109/ECCE47101.2021.9595113>, boosting RWNN, stacking RWNN, and ensemble deep RWNN, Shi et al. (2021) <doi:10.1016/j.patcog.2021.107978>.

Datasets and utility functions to support the book "R for Plant Disease Epidemiology" (R4PDE). It includes functions for quantifying disease, assessing spatial patterns, and modeling plant disease epidemics based on weather predictors. These tools are intended for teaching and research in plant disease epidemiology. Several functions are based on classical and contemporary methods, including those discussed in Laurence V. Madden, Gareth Hughes, and Frank van den Bosch (2007) <doi:10.1094/9780890545058>.

Access and handle APIs that use the international open311 GeoReport v2 standard for civic issue tracking <https://wiki.open311.org/GeoReport_v2/>. Retrieve civic service types and request data. Select and add available open311 endpoints and jurisdictions. Implicitly supports custom queries and open311 extensions. Requires a minimal number of hard dependencies while still allowing the integration in common R formats ('xml2', tibble', sf').

Ensemble model, for classification, regression and unsupervised learning, based on a forest of unpruned and randomized binary decision trees. Each tree is grown by sampling, with replacement, a set of variables at each node. Each cut-point is generated randomly, according to the continuous Uniform distribution. For each tree, data are either bootstrapped or subsampled. The unsupervised mode introduces clustering, dimension reduction and variable importance, using a three-layer engine. Random Uniform Forests are mainly aimed to lower correlation between trees (or trees residuals), to provide a deep analysis of variable importance and to allow native distributed and incremental learning.

For the calculation of sample size or power in a two-group repeated measures design, accounting for attrition and accommodating a variety of correlation structures for the repeated measures; details of the method can be found in the scientific paper: Donald Hedeker, Robert D. Gibbons, Christine Waternaux (1999) <doi:10.3102/10769986024001070>.

This package provides Rcpp bindings for cpptimer', a simple tic-toc timer class for benchmarking C++ code <https://github.com/BerriJ/cpptimer>. It's not just simple, it's blazing fast! This sleek tic-toc timer class supports overlapping timers as well as OpenMP parallelism <https://www.openmp.org/>. It boasts a nanosecond-level time resolution. We did not find any overhead of the timer itself at this resolution. Results (with summary statistics) are automatically passed back to R as a data frame.

Presentation-ready results tables for epidemiologists in an automated, reproducible fashion. The user provides the final analytical dataset and specifies the design of the table, with rows and/or columns defined by exposure(s), effect modifier(s), and estimands as desired, allowing to show descriptors and inferential estimates in one table -- bridging the rift between epidemiologists and their data, one table at a time. See Rothman (2017) <doi:10.1007/s10654-017-0314-3>.

An expansion of R's stats random wishart matrix generation. This package allows the user to generate singular, Uhlig and Harald (1994) <doi:10.1214/aos/1176325375>, and pseudo wishart, Diaz-Garcia, et al.(1997) <doi:10.1006/jmva.1997.1689>, matrices. In addition the user can generate wishart matrices with fractional degrees of freedom, Adhikari (2008) <doi:10.1061/(ASCE)0733-9399(2008)134:12(1029)>, commonly used in volatility modeling. Users can also use this package to create random covariance matrices.

This package provides data structures and functions for file input/output in the ribios software suite, supporting common bioinformatics and computational biology file formats, designed for fast loading and high performance with minimal dependencies.

This package provides tools to help with shiny reactivity. The react object offers an alternative way to call reactive expressions to better identify them in the server code.

For a multisite replication project, computes the consistency metric P_orig, which is the probability that the original study would observe an estimated effect size as extreme or more extreme than it actually did, if in fact the original study were statistically consistent with the replications. Other recommended metrics are: (1) the probability of a true effect of scientifically meaningful size in the same direction as the estimate the original study; and (2) the probability of a true effect of meaningful size in the direction opposite the original study's estimate. These two can be computed using the package \codeMetaUtility::prop_stronger. Additionally computes older metrics used in replication projects (namely expected agreement in "statistical significance" between an original study and replication studies as well as prediction intervals for the replication estimates). See Mathur and VanderWeele (under review; <https://osf.io/apnjk/>) for details.

Learning modules for reliability analysis including modules for Reliability, Availability, and Maintainability (RAM) Analysis, Life Data Analysis, and Reliability Testing.

Iterative least cost path and minimum spanning tree methods for projecting forest road networks. The methods connect a set of target points to an existing road network using igraph <https://igraph.org> to identify least cost routes. The cost of constructing a road segment between adjacent pixels is determined by a user supplied weight raster and a weight function; options include the average of adjacent weight raster values, and a function of the elevation differences between adjacent cells that penalizes steep grades. These road network projection methods are intended for integration into R workflows and modelling frameworks used for forecasting forest change, and can be applied over multiple time-steps without rebuilding a graph at each time-step.

Function for adapting the shape of the random walk Metropolis proposal as specified by robust adaptive Metropolis algorithm by Vihola (2012) <doi:10.1007/s11222-011-9269-5>. The package also includes fast functions for rank-one Cholesky update and downdate. These functions can be used directly from R or the corresponding C++ header files can be easily linked to other R packages.

This package implements and enhances the estimation techniques described in Rousseeuw & Verboven (2002) <doi:10.1016/S0167-9473(02)00078-6> for the location and scale of very small samples.

Utility functions to retrieve data from the UK National River Flow Archive (<https://nrfa.ceh.ac.uk/>, terms and conditions: <https://nrfa.ceh.ac.uk/help/costs-terms-and-conditions>). The package contains R wrappers to the UK NRFA data temporary-API. There are functions to retrieve stations falling in a bounding box, to generate a map and extracting time series and general information. The package is fully described in Vitolo et al (2016) "rnrfa: An R package to Retrieve, Filter and Visualize Data from the UK National River Flow Archive" <https://journal.r-project.org/archive/2016/RJ-2016-036/RJ-2016-036.pdf>.

These tools help you to assess if a corporate lending portfolio aligns with climate goals. They summarize key climate indicators attributed to the portfolio (e.g. production, emission factors), and calculate alignment targets based on climate scenarios. They implement in R the last step of the free software PACTA (Paris Agreement Capital Transition Assessment; <https://www.transitionmonitor.com/>). Financial institutions use PACTA to study how their capital allocation decisions align with climate change mitigation goals.

Algorithms for the spatial stratification of landscapes, sampling and modeling of spatially-varying phenomena. These algorithms offer a simple framework for the stratification of geographic space based on raster layers representing landscape factors and/or factor scales. The stratification process follows a hierarchical approach, which is based on first level units (i.e., classification units) and second-level units (i.e., stratification units). Nonparametric techniques allow to measure the correspondence between the geographic space and the landscape configuration represented by the units. These correspondence metrics are useful to define sampling schemes and to model the spatial variability of environmental phenomena. The theoretical background of the algorithms and code examples are presented in Fuentes et al. (2022). <doi:10.32614/RJ-2022-036>.

Generates tile maps for the East Caucasian language family, inspired by the Typological Atlas of the Languages of Daghestan (TALD, <https://lingconlab.ru/tald/>). It leverages ggplot2 to create visually informative maps, displaying rectangles for each language and allowing for color-coding based on linguistic features. The package includes a built-in dataset of 56 languages and the template for their distribution and provides flexibility to customize the tile map's appearance. The default template can be modified via the ability to hide or rename languages. It's designed to be used with external data tables containing language information and features, offering a tool for visualizing the geographic distribution and linguistic characteristics of East Caucasian languages.

Generates a project and repo for easy initialization of a GitHub repo for R workshops. The repo includes a README with instructions to ensure that all users have the needed packages, an RStudio project with the right directories and the proper data. The repo can then be used for hosting code taught during the workshop.

Robust tests (RW, RPB and RGF) are provided for testing the equality of several long-tailed symmetric (LTS) means when the variances are unknown and arbitrary. RW, RPB and RGF tests are robust versions of Welch's F test proposed by Welch (1951) <doi:10.2307/2332579>, parametric bootstrap test proposed by Krishnamoorthy et. al (2007) <doi:10.1016/j.csda.2006.09.039>; and generalized F test proposed by Weerahandi (1995) <doi:10.2307/2532947>;, respectively. These tests are based on the modified maximum likelihood (MML) estimators proposed by Tiku(1967, 1968) <doi:10.2307/2333859>, <doi:10.1080/01621459.1968.11009228>.