Formats for R Markdown that undo modifications by pandoc and rmarkdown to original latex templates, such as smaller margins, paragraph spacing, and compact titles. In addition, enhancements such as author blocks with affiliations and headers and footers are introduced. All of this functionality is built around plugins that modify the default pandoc template without relying on custom templates.

Convenience functions to make some common tasks with right-to-left string printing easier, more convenient and with no need to remember long Unicode characters. Specifically helpful for right-to-left languages such as Arabic, Persian and Hebrew.

This package provides a toolkit for analyzing classifier performance by using receiver operating characteristic (ROC) curves. Performance may be assessed on a single classifier or multiple ones simultaneously, making it suitable for comparisons. In addition, different metrics allow the evaluation of local performance when working within restricted ranges of sensitivity and specificity. For details on the different implementations, see McClish D. K. (1989) <doi:10.1177/0272989X8900900307>, Vivo J.-M., Franco M. and Vicari D. (2018) <doi:10.1007/S11634-017-0295-9>, Jiang Y., et al (1996) <doi:10.1148/radiology.201.3.8939225>, Franco M. and Vivo J.-M. (2021) <doi:10.3390/math9212826> and Carrington, André M., et al (2020) <doi: 10.1186/s12911-019-1014-6>.

This package provides a parallel function for multivariate outlier detection named modified Stahel-Donoho estimators is contained in this package. The function RMSDp() is for elliptically distributed datasets and recognizes outliers based on Mahalanobis distance. This function is for higher dimensional datasets that cannot be handled by a single core function RMSD() included in RMSD package. See Wada and Tsubaki (2013) <doi:10.1109/CLOUDCOM-ASIA.2013.86> for the detail of the algorithm.

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.

This package provides a fast calculation of the Blyth-Still-Casella confidence interval. The implementation follows the StatXact 9 manual (Cytel 2010) and "Refining Binomial Confidence Intervals" by George Casella (1986) <doi:10.2307/3314658>.

This package provides a comprehensive suite of statistical tools for Quality Management, designed around the Define, Measure, Analyze, Improve, and Control (DMAIC) cycle used in Six Sigma methodology. Based on the discontinued CRAN package qualitytools', this package refactors its original design by incorporating R6 object-oriented programming for increased flexibility and performance. It replaces traditional graphics with modern, interactive visualizations using ggplot2 and plotly'. Built on tidyverse principles, it simplifies data manipulation and visualization, offering an intuitive approach to quality science.

The use of proxies is required in certain network environments. Despite the power of system level software, it is still inconvenient to switch proxy networks at random in R's console. This package is designed to provide one-click switching between proxy and non-proxy states.

Interface around JDemetra+ (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System (ESS) and the European System of Central Banks. It offers full access to all options and outputs of JDemetra+', including the two leading seasonal adjustment methods TRAMO/SEATS+ and X-12ARIMA/X-13ARIMA-SEATS.

Sets a significance level for Random Forest MDI (Mean Decrease in Impurity, Gini or sum of squares) variable importance scores, using an empirical Bayes approach. See Dunne et al. (2022) <doi:10.1101/2022.04.06.487300>.

This package provides an easy way to compute the Theil Sehn Regression method and also the Siegel Regression Method which are both robust methods base on the median of slopes between all pairs of data. In contrast with the least squared linear regression, these methods are not sensitive to outliers. Theil, H. (1992) <doi:10.1007/978-94-011-2546-8_20>, Sen, P. K. (1968) <doi:10.1080/01621459.1968.10480934>.

JDemetra+ (<https://github.com/jdemetra/jdemetra-app>) is the seasonal adjustment software officially recommended to the members of the European Statistical System and the European System of Central Banks. Seasonal adjustment models performed with JDemetra+ can be stored into workspaces. JWSACruncher (<https://github.com/jdemetra/jwsacruncher/releases> for v2 and <https://github.com/jdemetra/jdplus-main/releases> for v3) is a console tool that re-estimates all the multi-processing defined in a workspace and to export the result. rjwsacruncher allows to launch easily the JWSACruncher'.

Allow function for using TGStat Stat API and TGStat Search API', for more details see <https://api.tgstat.ru/docs/ru/start/intro.html>. TGStat provide telegram channel analytics data.

This package provides functions to generate plots and tables for comparing independently- sampled populations. Companion package to "A Primer on Visualizations for Comparing Populations, Including the Issue of Overlapping Confidence Intervals" by Wright, Klein, and Wieczorek (2019) <DOI:10.1080/00031305.2017.1392359> and "A Joint Confidence Region for an Overall Ranking of Populations" by Klein, Wright, and Wieczorek (2020) <DOI:10.1111/rssc.12402>.

R interface to access prices and market data with the Bloomberg Data License service from <https://www.bloomberg.com/professional/product/data-license/>. As a prerequisite, a valid Data License from Bloomberg is needed together with the corresponding SFTP credentials and whitelisting of the IP from which accessing the service. This software and its author are in no way affiliated, endorsed, or approved by Bloomberg or any of its affiliates. Bloomberg is a registered trademark.

Import data written in the JCAMP-DX format. This is an instrument-independent format used in the field of spectroscopy. Examples include IR, NMR, and Raman spectroscopy. See the vignette for background and supported formats. The official JCAMP-DX site is <http://www.jcamp-dx.org/>.

Construct an explainable nomogram for a machine learning (ML) model to improve availability of an ML prediction model in addition to a computer application, particularly in a situation where a computer, a mobile phone, an internet connection, or the application accessibility are unreliable. This package enables a nomogram creation for any ML prediction models, which is conventionally limited to only a linear/logistic regression model. This nomogram may indicate the explainability value per feature, e.g., the Shapley additive explanation value, for each individual. However, this package only allows a nomogram creation for a model using categorical without or with single numerical predictors. Detailed methodologies and examples are documented in our vignette, available at <https://htmlpreview.github.io/?https://github.com/herdiantrisufriyana/rmlnomogram/blob/master/doc/ml_nomogram_exemplar.html>.

This package provides functions for reconstructing individual-level data (time, status, arm) from Kaplan-MEIER curves published in academic journals (e.g. NEJM, JCO, JAMA). The individual-level data can be used for re-analysis, meta-analysis, methodology development, etc. This package was used to generate the data for commentary such as Sun, Rich, & Wei (2018) <doi:10.1056/NEJMc1808567>. Please see the vignette for a quickstart guide.

An R API Client for Valve's Dota2. RDota2 can be easily used to connect to the Steam API and retrieve data for Valve's popular video game Dota2. You can find out more about Dota2 at <http://store.steampowered.com/app/570/>.

Tests linear regressions for significance reversal through leave-one(multiple)-out.

Includes sysdata.rda file for packages of the RobASt - family of packages; is currently used by package RobExtremes only.

This package performs kernel based estimates on in-memory raster images from the raster package. These kernel estimates include local means variances, modes, and quantiles. All results are in the form of raster images, preserving original resolution and projection attributes.

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.

Exploit controlled vocabularies organized on tematres servers.