This package provides a foreach parallel adapter for parabar backends. This package offers a minimal implementation of the %dopar% operator, enabling users to run foreach loops in parallel, leveraging the parallel and progress-tracking capabilities of the parabar package. Learn more about parabar and doParabar at <https://parabar.mihaiconstantin.com>.

Allows for export of DiagrammeR Graphviz objects to SVG.

An interactive image editing tool that can be added as part of the HTML in Shiny, R markdown or any type of HTML document. Often times, plots, photos are embedded in the web application/file. drawer can take screenshots of these image-like elements, or any part of the HTML document and send to an image editing space called canvas to allow users immediately edit the screenshot(s) within the same document. Users can quickly combine, compare different screenshots, upload their own images and maybe make a scientific figure.

Datasets and functions to accompany the book Analisis de datos con el programa estadistico R: una introduccion aplicada by Salas-Eljatib (2021, ISBN: 9789566086109). The package helps carry out data management, exploratory analyses, and model fitting.

This package provides a set of user-friendly wrapper functions for creating consistent graphics and diagrams with lines, common shapes, text, and page settings. Compatible with and based on the R grid package.

This package provides a collection of widely used univariate data sets of various applied domains on applications of distribution theory. The functions allow researchers and practitioners to quickly, easily, and efficiently access and use these data sets. The data are related to different applied domains and as follows: Bio-medical, survival analysis, medicine, reliability analysis, hydrology, actuarial science, operational research, meteorology, extreme values, quality control, engineering, finance, sports and economics. The total 100 data sets are documented along with associated references for further details and uses.

The Dirichlet Laplace shrinkage prior in Bayesian linear regression and variable selection, featuring: utility functions in implementing Dirichlet-Laplace priors such as visualization; scalability in Bayesian linear regression; penalized credible regions for variable selection.

Perform tree-ring analyses such as detrending, chronology building, and cross dating. Read and write standard file formats used in dendrochronology.

Exploratory analysis of a data base. Using the functions of this package is possible to filter the data set detecting atypical values (outliers) and to perform exploratory analysis through visual inspection or dispersion measures. With this package you can explore the structure of your data using several parameters at the same time joining statistical parameters with different graphics. Finally, this package aid to confirm or reject the hypothesis that your data structure presents a normal distribution. Therefore this package is useful to get a previous insight of your data before to carry out statistical analysis.

The set of teacher/class lessons is completed with a column that allocates a day to each lesson, so that the distribution of lessons by day, by class, and by teacher is as uniform as possible. <https://vlad.bazon.net/>.

Data quality assessments guided by a data quality framework introduced by Schmidt and colleagues, 2021 <doi:10.1186/s12874-021-01252-7> target the data quality dimensions integrity, completeness, consistency, and accuracy. The scope of applicable functions rests on the availability of extensive metadata which can be provided in spreadsheet tables. Either standardized (e.g. as html5 reports) or individually tailored reports can be generated. For an introduction into the specification of corresponding metadata, please refer to the package website <https://dataquality.qihs.uni-greifswald.de/VIN_Annotation_of_Metadata.html>.

Several quality measurements for investigating the performance of dimensionality reduction methods are provided here. In addition a new quality measurement called Gabriel classification error is made accessible, which was published in Thrun, M. C., Märte, J., & Stier, Q: "Analyzing Quality Measurements for Dimensionality Reduction" (2023), Machine Learning and Knowledge Extraction (MAKE), <DOI:10.3390/make5030056>.

An efficient and convenient set of functions to perform differential network estimation through the use of alternating direction method of multipliers optimization with a variety of loss functions.

Summarise patient-level drug utilisation cohorts using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. New users and prevalent users cohorts can be generated and their characteristics, indication and drug use summarised.

This package provides a system for extracting news from Chilean media, specifically through Web Scapping from Chilean media. The package allows for news searches using search phrases and date filters, and returns the results in a structured format, ready for analysis. Additionally, it includes functions to clean the extracted data, visualize it, and store it in databases. All of this can be done automatically, facilitating the collection and analysis of relevant information from Chilean media.

This package creates testthat tests from roxygen examples using simple tags.

This package provides a set of functions to perform distribution-free Bayesian analyses. Included are Bayesian analogues to the frequentist Mann-Whitney U test, the Wilcoxon Signed-Ranks test, Kendall's Tau Rank Correlation Coefficient, Goodman and Kruskal's Gamma, McNemar's Test, the binomial test, the sign test, the median test, as well as distribution-free methods for testing contrasts among condition and for computing Bayes factors for hypotheses. The package also includes procedures to estimate the power of distribution-free Bayesian tests based on data simulations using various probability models for the data. The set of functions provide data analysts with a set of Bayesian procedures that avoids requiring parametric assumptions about measurement error and is robust to problem of extreme outlier scores.

Measure of agreement delta was originally by Martà n & Femia (2004) <DOI:10.1348/000711004849268>. Since then has been considered as agreement measure for different fields, since their behavior is usually better than the usual kappa index by Cohen (1960) <DOI:10.1177/001316446002000104>. The main issue with delta is that can not be computed by hand contrary to kappa. The current algorithm is based on the Version 5 of the delta windows program that can be found on <https://www.ugr.es/~bioest/software/delta/cmd.php?seccion=downloads>.

You can load a schema from a DTR (data type registry) as an R object. Use this schema to write your data in JSON-LD (JavaScript Object Notation for Linked Data) format to make it machine readable.

This package provides a simple interface to build designs using the package DeclareDesign'. In one line of code, users can specify the parameters of individual designs and diagnose their properties. The designers can also be used to compare performance of a given design across a range of combinations of parameters, such as effect size, sample size, and assignment probabilities.

Generate reports that enable quick visual review of temporal shifts in record-level data. Time series plots showing aggregated values are automatically created for each data field (column) depending on its contents (e.g. min/max/mean values for numeric data, no. of distinct values for categorical data), as well as overviews for missing values, non-conformant values, and duplicated rows. The resulting reports are shareable and can contribute to forming a transparent record of the entire analysis process. It is designed with Electronic Health Records in mind, but can be used for any type of record-level temporal data (i.e. tabular data where each row represents a single "event", one column contains the "event date", and other columns contain any associated values for the event).

Discrete event simulation (DES) involves modeling of systems having discrete, i.e. abrupt, state changes. For instance, when a job arrives to a queue, the queue length abruptly increases by 1. This package is an R implementation of the event-oriented approach to DES; see the tutorial in Matloff (2008) <http://heather.cs.ucdavis.edu/~matloff/156/PLN/DESimIntro.pdf>.

Implementation of the Decorrelated Local Linear estimator proposed in <arxiv:1907.12732>. It constructs the confidence interval for the derivative of the function of interest under the high-dimensional sparse additive model.

Implementation of three methods based on the diversity forest (DF) algorithm (Hornung, 2022, <doi:10.1007/s42979-021-00920-1>), a split-finding approach that enables complex split procedures in random forests. The package includes: 1. Interaction forests (IFs) (Hornung & Boulesteix, 2022, <doi:10.1016/j.csda.2022.107460>): Model quantitative and qualitative interaction effects using bivariable splitting. Come with the Effect Importance Measure (EIM), which can be used to identify variable pairs that have well-interpretable quantitative and qualitative interaction effects with high predictive relevance. 2. Two random forest-based variable importance measures (VIMs) for multi-class outcomes: the class-focused VIM, which ranks covariates by their ability to distinguish individual outcome classes from the others, and the discriminatory VIM, which measures overall covariate influence irrespective of class-specific relevance. 3. The basic form of diversity forests that uses conventional univariable, binary splitting (Hornung, 2022). Except for the multi-class VIMs, all methods support categorical, metric, and survival outcomes. The package includes visualization tools for interpreting the identified covariate effects. Built as a fork of the ranger R package (main author: Marvin N. Wright), which implements random forests using an efficient C++ implementation.