This companion package extends the package robmed (Alfons, Ates & Groenen, 2022b; <doi:10.18637/jss.v103.i13>) in various ways. Most notably, it provides a graphical user interface for the robust bootstrap test ROBMED (Alfons, Ates & Groenen, 2022a; <doi:10.1177/1094428121999096>) to make the method more accessible to less proficient R users, as well as functions to export the results as a table in a Microsoft Word or Microsoft Powerpoint document, or as a LaTeX table. Furthermore, the package contains a shiny app to compare various bootstrap procedures for mediation analysis on simulated data.

This package provides a client for the API of OpenDota. OpenDota is a web service which is provide DOTA2 real time data. Data is collected through the Steam WebAPI. With ROpenDota you can easily grab the latest DOTA2 statistics in R programming such as latest match on official international competition, analyzing your or enemy performance to learn their strategies,etc. Please see <https://github.com/rosdyana/ROpenDota> for more information.

Implementation of the following methods for event history analysis. Risk regression models for survival endpoints also in the presence of competing risks are fitted using binomial regression based on a time sequence of binary event status variables. A formula interface for the Fine-Gray regression model and an interface for the combination of cause-specific Cox regression models. A toolbox for assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance is measured by the Brier score and the area under the ROC curve for binary possibly time-dependent outcome. Inverse probability of censoring weighting and pseudo values are used to deal with right censored data. Lists of risk markers and lists of risk models are assessed simultaneously. Cross-validation repeatedly splits the data, trains the risk prediction models on one part of each split and then summarizes and compares the performance across splits.

Calculation of ratios between two data sets containing environmental data like element concentrations by different methods. Additionally plant element concentrations can be corrected for adhering particles (soil, airborne dust).

This package provides a very lightweight package that writes out log messages in an opinionated way. Simpler and lighter than other logging packages, rlog provides a compact feature set that focuses on getting the job done in a Unix-like way.

Traditional noise filtering methods aim at removing noisy samples from a classification dataset. This package adapts classic and recent filtering techniques for use in regression problems, and it also incorporates methods specifically designed for regression data. In order to do this, it uses approaches proposed in the specialized literature, such as Martin et al. (2021) [<doi:10.1109/ACCESS.2021.3123151>] and Arnaiz-Gonzalez et al. (2016) [<doi:10.1016/j.eswa.2015.12.046>]. Thus, the goal of the implemented noise filters is to eliminate samples with noise in regression datasets.

An algorithm is proposed to estimate regression kink model proposed by the paper, Lixiong Yang and Jen-Je Su (2018) <doi:10.1016/j.jimonfin.2018.06.002>.

This package performs genome-wide association studies (GWAS) on individuals that are both related and have repeated measurements. For each Single Nucleotide Polymorphism (SNP), it computes score statistic based p-values for a linear mixed model including random polygenic effects and a random effect for repeated measurements. The computed p-values can be visualized in a Manhattan plot. For more details see Ronnegard et al. (2016) <doi:10.1111/2041-210X.12535> and for more examples see <https://github.com/larsronn/RepeatABEL_Tutorials>.

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.

An Rcpp interface for Eunjeon project <http://eunjeon.blogspot.com/>. The mecab-ko and mecab-ko-dic is based on a C++ library, and part-of-speech tagging with them is useful when the spacing of source Korean text is not correct. This package provides part-of-speech tagging and tokenization function for Korean text.

R Markdown output formats based on JavaScript libraries such as Scrollama (<https://github.com/russellsamora/scrollama>) for storytelling.

This package provides several non parametric randomness tests for numeric sequences.

An implementation of robust boosting algorithms for regression in R. This includes the RRBoost method proposed in the paper "Robust Boosting for Regression Problems" (Ju X and Salibian-Barrera M. 2020) <doi:10.1016/j.csda.2020.107065>. It also implements previously proposed boosting algorithms in the simulation section of the paper: L2Boost, LADBoost, MBoost (Friedman, J. H. (2001) <doi:10.1214/aos/1013203451>) and Robloss (Lutz et al. (2008) <doi:10.1016/j.csda.2007.11.006>).

Reads in continuous glucose monitor data of many different formats, calculates a host of glycemic variability metrics, and plots glucose over time.

This package contains tools for working with and analyzing hospital readmissions data. The package provides utilities for components of the Hospital Readmissions Reduction Program (HRRP), including program timeline functions, Hospital-Specific Report (HSR) helpers, and general importing tools for the Provider Data Catalog (PDC).

Reliable and flexible tools for scoring redistricting plans using common measures and metrics. These functions provide key direct access to tools useful for non-simulation analyses of redistricting plans, such as for measuring compactness or partisan fairness. Tools are designed to work with the redist package seamlessly.

This package provides a programmatic interface to web-services of YouTheria. YouTheria is an online database of mammalian trait data <http://www.utheria.org/>.

R Interface to JDemetra+ 3.x (<https://github.com/jdemetra>) time series analysis software. It offers full access to options and outputs of X-13', including Reg-ARIMA modelling (automatic AutoRegressive Integrated Moving Average (ARIMA) model with outlier detection and trading days adjustment) and X-11 decomposition.

This package provides a Bayesian companion to the rms package, rmsb provides Bayesian model fitting, post-fit estimation, and graphics. It implements Bayesian regression models whose fit objects can be processed by rms functions such as contrast()', summary()', Predict()', nomogram()', and latex()'. The fitting function currently implemented in the package is blrm() for Bayesian logistic binary and ordinal regression with optional clustering, censoring, and departures from the proportional odds assumption using the partial proportional odds model of Peterson and Harrell (1990) <https://www.jstor.org/stable/2347760>.

Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases). Please refer to Weber et al. (2021) <doi:10.18637/jss.v100.i19> for details on applying this package while Neuenschwander et al. (2010) <doi:10.1177/1740774509356002> and Schmidli et al. (2014) <doi:10.1111/biom.12242> explain details on the methodology.

Biologically relevant, yet mathematically sound constraints are used to compute the propensity and thence infer the dominant direction of reactions of a generic biochemical network. The reactions must be unique and their number must exceed that of the reactants,i.e., reactions >= reactants + 2. ReDirection', computes the null space of a user-defined stoichiometry matrix. The spanning non-zero and unique reaction vectors (RVs) are combinatorially summed to generate one or more subspaces recursively. Every reaction is represented as a sequence of identical components across all RVs of a particular subspace. The terms are evaluated with (biologically relevant bounds, linear maps, tests of convergence, descriptive statistics, vector norms) and the terms are classified into forward-, reverse- and equivalent-subsets. Since, these are mutually exclusive the probability of occurrence is binary (all, 1; none, 0). The combined propensity of a reaction is the p1-norm of the sub-propensities, i.e., sum of the products of the probability and maximum numeric value of a subset (least upper bound, greatest lower bound). This, if strictly positive is the probable rate constant, is used to infer dominant direction and annotate a reaction as "Forward (f)", "Reverse (b)" or "Equivalent (e)". The inherent computational complexity (NP-hard) per iteration suggests that a suitable value for the number of reactions is around 20. Three functions comprise ReDirection. These are check_matrix() and reaction_vector() which are internal, and calculate_reaction_vector() which is external.

Implementation of the metalog distribution in R. The metalog distribution is a modern, highly flexible, data-driven distribution. Metalogs are developed by Keelin (2016) <doi:10.1287/deca.2016.0338>. This package provides functions to build these distributions from raw data. Resulting metalog objects are then useful for exploratory and probabilistic analysis.

This is an R wrapper from the AWS Command Line Interface that provides methods to manage the user configuration on Amazon Web Service. You can create as many profiles as you want, manage them, and delete them. The profiles created with this tool work with all AWS products such as S3, Glacier, and EC2. It also provides a function to automatically install AWS CLI, but you can download it and install it manually if you prefer.

Climacell is a weather platform that provides hyper-local forecasts and weather data. This package enables the user to query the core layers of the time line interface of the Climacell v4 API <https://www.climacell.co/weather-api/>. This package requires a valid API key. See vignettes for instructions on use.