This package provides methods for comparing different regression algorithms for describing the temporal dynamics of secondary tree growth (xylem and phloem). Users can compare the accuracy of the most common fitting methods usually used to analyse xylem and phloem data, i.e., Gompertz function, Double Gompertz function, General Additive Models (GAMs); and an algorithm newly introduced to the field, i.e., Bayesian Regularised Neural Networks (brnn). The core function of the package is XPSgrowth(), while the results can be interpreted using implemented generic S3 methods, such as plot() and summary().

This package performs exploratory projection pursuit via REPPlab (Daniel Fischer, Alain Berro, Klaus Nordhausen & Anne Ruiz-Gazen (2019) <doi:10.1080/03610918.2019.1626880>) using a Shiny app.

An implementation of the radviz projection in R. It enables the visualization of multidimensional data while maintaining the relation to the original dimensions. This package provides functions to create and plot radviz projections, and a number of summary plots that enable comparison and analysis. For reference see Hoffman *et al.* (1999) (<doi:10.1145/331770.331775>) for original implementation, see Di Caro *et al* (2012) (<doi:10.1007/978-3-642-13672-6_13>), for the original method for dimensional anchor arrangements, see Demsar *et al.* (2007) (<doi:10.1016/j.jbi.2007.03.010>) for the original Freeviz implementation.

Captures errors encountered when running run_examples()', and processes and archives them. The function run_examples() within the devtools package allows batch execution of all of the examples within a given package. This is much more convenient than testing each example manually. However, a major inconvenience is that if an error is encountered, the program stops and does not complete testing the remaining examples. Also, there is not a systematic record of the results, namely which package functions had no examples, which had examples that failed, and which had examples that succeeded. The current package provides the missing functionality.

Show physics, math and engineering students how an ODE solver is made and how effective R classes can be for the construction of the equations that describe natural phenomena. Inspiration for this work comes from the book on "Computer Simulations in Physics" by Harvey Gould, Jan Tobochnik, and Wolfgang Christian. Book link: <http://www.compadre.org/osp/items/detail.cfm?ID=7375>.

Extends R Commander with a unified menu of new and pre-existing statistical functions related to public management and policy analysis statistics. Functions and menus have been renamed according to the usage in PMGT 630 in the Master of Public Administration program at Brigham Young University.

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

This package provides reference classes implementing some useful data structures. The package implements these data structures by using the reference class R6. Therefore, the classes of the data structures are also reference classes which means that their instances are passed by reference. The implemented data structures include stack, queue, double-ended queue, doubly linked list, set, dictionary and binary search tree. See for example <https://en.wikipedia.org/wiki/Data_structure> for more information about the data structures.

This is a meta-package designed to support the installation of Rmosek (>= 6.0) and bring the optimization facilities of MOSEK (>= 6.0) to the R-language. The interface supports large-scale optimization of many kinds: Mixed-integer and continuous linear, second-order cone, exponential cone and power cone optimization, as well as continuous semidefinite optimization. Rmosek and the R-language are open-source projects. MOSEK is a proprietary product, but unrestricted trial and academic licenses are available.

This package provides a client package that makes the KorAP web service API accessible from R. The corpus analysis platform KorAP has been developed as a scientific tool to make potentially large, stratified and multiply annotated corpora, such as the German Reference Corpus DeReKo or the Corpus of the Contemporary Romanian Language CoRoLa', accessible for linguists to let them verify hypotheses and to find interesting patterns in real language use. The RKorAPClient package provides access to KorAP and the corpora behind it for user-created R code, as a programmatic alternative to the KorAP web user-interface. You can learn more about KorAP and use it directly on DeReKo at <https://korap.ids-mannheim.de/>.

Imports data from the SurveyXact commercial service <https://rambollxact.com>, adds variable labels, and converts value labels to factors in the same order as exported from SurveyXact'.

This package provides functions to convert Rd to roxygen documentation. It can parse an Rd file to a list, create the roxygen documentation and update the original R script (e.g. the one containing the definition of the function) accordingly. This package also provides utilities that can help developers build packages using roxygen more easily. The formatR package can be used to reformat the R code in the examples sections so that the code will be more readable.

This package provides tools for molecule-oriented and reaction-centred analysis of root exudate datasets. It supports structural matching based on PubChem', calculation of molecular descriptors, and inference of candidate microbe-associated metabolic reactions using Kyoto Encyclopedia of Genes and Genomes ('KEGG') identifiers and Enzyme Commission ('EC') numbers. For background on these databases, see Kanehisa et al. (2023) <doi:10.1093/nar/gkac963> and Kim et al. (2023) <doi:10.1093/nar/gkac956>.

T (extent of the primary tumor), N (absence or presence and extent of regional lymph node metastasis) and M (absence or presence of distant metastasis) are three components to describe the anatomical tumor extent. TNM stage is important in treatment decision-making and outcome predicting. The existing oropharyngeal Cancer (OPC) TNM stages have not made distinction of the two sub sites of Human papillomavirus positive (HPV+) and Human papillomavirus negative (HPV-) diseases. We developed novel criteria to assess performance of the TNM stage grouping schemes based on parametric modeling adjusting on important clinical factors. These criteria evaluate the TNM stage grouping scheme in five different measures: hazard consistency, hazard discrimination, explained variation, likelihood difference, and balance. The methods are described in Xu, W., et al. (2015) <https://www.austinpublishinggroup.com/biometrics/fulltext/biometrics-v2-id1014.php>.

Inspired by Karl Broman`s reader on using knitr with asciidoc (<https://kbroman.org/knitr_knutshell/pages/asciidoc.html>), this is merely a wrapper to knitr and asciidoc'.

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 Synthesize Bio models from their API <https://app.synthesize.bio/> using this wrapper that provides a convenient interface to the Synthesize Bio API, allowing users to generate realistic gene expression data based on specified biological conditions. This package enables researchers to easily access AI-generated transcriptomic data for various modalities including bulk RNA-seq, single-cell RNA-seq, microarray data, and more.

This package provides an R interface to the ROCEEH Out of Africa Database (ROAD) (<https://www.roceeh.uni-tuebingen.de/roadweb/smarty_road_simple_search.php>), a comprehensive resource for archaeological, anthropological, paleoenvironmental and geographic data from Africa and Eurasia dating from 3,000,000 to 20,000 years BP. The package allows users to retrieve data from the online database at different levels of detail and customize search requests. Functions return `data frame` objects compatible with other R packages used in prehistoric and paleoenvironmental science, supporting reproducible workflows as an input provider.

This package performs Random Subspace Method (RSM) for high-dimensional linear regression to obtain variable importance measures. The final model is chosen based on validation set or Generalized Information Criterion.

Determination of rainfall-runoff erosivity factor.

Provide simple mechanism to repeatedly evaluate an expression until either it succeeds or timeout exceeded. It is useful in situations that random failures could happen.

This package provides a RUT (Rol Unico Tributario) is an unique and personal identification number implemented in Chile to identify citizens and taxpayers. Rutifier allows to validate if a RUT exist or not and change between the different formats a RUT can have.

Three robust marginal integration procedures for additive models based on local polynomial kernel smoothers. As a preliminary estimator of the multivariate function for the marginal integration procedure, a first approach uses local constant M-estimators, a second one uses local polynomials of order 1 over all the components of covariates, and the third one uses M-estimators based on local polynomials but only in the direction of interest. For this last approach, estimators of the derivatives of the additive functions can be obtained. All three procedures can compute predictions for points outside the training set if desired. See Boente and Martinez (2017) <doi:10.1007/s11749-016-0508-0> for details.

This package provides access to a suite of geospatial data layers for wildfire management, fuel modeling, ecology, natural resource management, climate, conservation, etc., via the LANDFIRE (<https://www.landfire.gov/>) Product Service ('LFPS') API.