Native R only allows PDF exports of reference manuals. The Rd2md package converts the package documentation files into markdown files and combines them into a markdown version of the package reference manual.

Efficient reading of raw markdown tables into tibbles. Designed to accept content from strings, files, and URLs with the ability to extract and read multiple tables from markdown for analysis.

This package provides a method for modeling robust generalized autoregressive conditional heteroskedasticity (Garch) (1,1) processes, providing robustness toward additive outliers instead of innovation outliers. This work is based on the methodology described by Muler and Yohai (2008) <doi:10.1016/j.jspi.2007.11.003>.

This package contains a function to randomize subjects, patients in groups of sequences (treatment sequences). If a blocksize is given, the randomization will be done within blocks. The randomization may be controlled by a Wald-Wolfowitz runs test. Functions to obtain the p-value of that test are included. The package is mainly intended for randomization of bioequivalence studies but may be used also for other clinical crossover studies. Contains two helper functions sequences() and williams() to get the sequences of commonly used designs in BE studies.

This package provides an interface to the Facebook API.

Quantitative Structure-Activity Relationship (QSAR) modeling is a valuable tool in computational chemistry and drug design, where it aims to predict the activity or property of chemical compounds based on their molecular structure. In this vignette, we present the rQSAR package, which provides functions for variable selection and QSAR modeling using Multiple Linear Regression (MLR), Partial Least Squares (PLS), and Random Forest algorithms.

Implementation of various spirometry equations in R, currently the GLI-2012 (Global Lung Initiative; Quanjer et al. 2012 <doi:10.1183/09031936.00080312>), the race-neutral GLI global 2022 (Global Lung Initiative; Bowerman et al. 2023 <doi:10.1164/rccm.202205-0963OC>), the NHANES3 (National Health and Nutrition Examination Survey; Hankinson et al. 1999 <doi:10.1164/ajrccm.159.1.9712108>) and the JRS 2014 (Japanese Respiratory Society; Kubota et al. 2014 <doi:10.1016/j.resinv.2014.03.003>) equations. Also the GLI-2017 diffusing capacity equations <doi:10.1183/13993003.00010-2017> are implemented. Contains user-friendly functions to calculate predicted and LLN (Lower Limit of Normal) values for different spirometric parameters such as FEV1 (Forced Expiratory Volume in 1 second), FVC (Forced Vital Capacity), etc, and to convert absolute spirometry measurements to percent (%) predicted and z-scores.

Utility functions for interacting with the COMPADRE and COMADRE databases of matrix population models. Described in Jones et al. (2021) <doi:10.1101/2021.04.26.441330>.

Truncated Newton function minimization with bounds constraints based on the Matlab'/'Octave codes of Stephen Nash.

Test for effects of both individual factors and their interaction on replicated spatial patterns in a two factorial design, as explained in Ramon et al. (2016) <doi:10.1111/ecog.01848>.

This package provides a programmatic interface to the Web Service methods provided by ITALIC (<https://italic.units.it>). ITALIC is a database of lichen data in Italy and bordering European countries. ritalic includes functions for retrieving information about lichen scientific names, geographic distribution, ecological data, morpho-functional traits and identification keys. More information about the data is available at <https://italic.units.it/?procedure=base&t=59&c=60>. The API documentation is available at <https://italic.units.it/?procedure=api>.

Download, inspect, reconcile, and summarize mammal taxonomic names with the Mammal Diversity Database (MDD). Supports accepted names, synonyms, original combinations, distribution summaries, and mapped outputs derived from packaged MDD releases. Designed for reproducible mammal name resolution workflows in R'.

Suite of tools for using D3', a library for producing dynamic, interactive data visualizations. Supports translating objects into D3 friendly data structures, rendering D3 scripts, publishing D3 visualizations, incorporating D3 in R Markdown, creating interactive D3 applications with Shiny, and distributing D3 based htmlwidgets in R packages.

Traditional latent variable models assume that the population is homogeneous, meaning that all individuals in the population are assumed to have the same latent structure. However, this assumption is often violated in practice given that individuals may differ in their age, gender, socioeconomic status, and other factors that can affect their latent structure. The robust expectation maximization (REM) algorithm is a statistical method for estimating the parameters of a latent variable model in the presence of population heterogeneity as recommended by Nieser & Cochran (2023) <doi:10.1037/met0000413>. The REM algorithm is based on the expectation-maximization (EM) algorithm, but it allows for the case when all the data are generated by the assumed data generating model.

Implementation of JQuery <https://jquery.com> and CSS styles to allow easy incorporation of various social media elements on a page. The elements include addition of share buttons or connect with us buttons or hyperlink buttons to Shiny applications or dashboards and Rmarkdown documents.Sharing capability on social media platforms including Facebook <https://www.facebook.com>, Linkedin <https://www.linkedin.com>, X/Twitter <https://x.com>, Tumblr <https://www.tumblr.com>, Pinterest <https://www.pinterest.com>, Whatsapp <https://www.whatsapp.com>, Reddit <https://www.reddit.com>, Baidu <https://www.baidu.com>, Blogger <https://www.blogger.com>, Weibo <https://www.weibo.com>, Instagram <https://www.instagram.com>, Telegram <https://www.telegram.me>, Youtube <https://www.youtube.com>.

Permite obtener rápidamente una serie de medidas de resumen y gráficos para datos numéricos discretos o continuos en series simples. También permite obtener tablas de frecuencia clásicas y gráficos cuando se desea realizar un análisis de series agrupadas. Su objetivo es de aplicación didáctica para un curso introductorio de Bioestadà stica utilizando el software R, para las carreras de grado las carreras de grado y otras ofertas educativas de la Facultad de Ciencias Agrarias de la UNJu / It generates summary measures and graphs for discrete or continuous numerical data in simple series. It also enables the creation of classic frequency tables and graphs when analyzing grouped series. Its purpose is for educational application in an introductory Biostatistics course using the R software, aimed at undergraduate programs and other educational offerings of the Faculty of Agricultural Sciences at the National University of Jujuy (UNJu).

This package provides a direct interface to the underlying XML representation of DDI Codebook 2.5 with flexible API creation.

This package provides clean, tidy access to climate and weather data from the National Oceanic and Atmospheric Administration ('NOAA') via the National Centers for Environmental Information ('NCEI') Data Service API <https://www.ncei.noaa.gov/access/services/data/v1>. Covers daily weather observations, monthly and annual summaries, and 30-year climate normals from over 100,000 stations across 180 countries. No API key is required. Dedicated functions handle the most common datasets, while a generic fetcher provides access to all NCEI datasets. Station discovery functions help users find stations by location or name. Data is downloaded on first use and cached locally for subsequent calls. This package is not endorsed or certified by NOAA'.

This package provides a data mining approach for longitudinal and clustered data, which combines the structure of mixed effects model with tree-based estimation methods. See Sela, R.J. and Simonoff, J.S. (2012) RE-EM trees: a data mining approach for longitudinal and clustered data <doi:10.1007/s10994-011-5258-3>.

R functions for the computation of the truncated maximum likelihood and the robust accelerated failure time regression for gaussian and log-Weibull case.

We visualize the standard deviation of a data set as the radius of a cylinder whose volume equals the total volume of several cylinders made by revolving the empirical cumulative distribution function about the vertical line through the mean. For more details see Sarkar and Rashid (2016) <doi:10.1080/00031305.2016.1165734>.

This package provides a memory-efficient, visualize-enhanced, parallel-accelerated Genome-Wide Association Study (GWAS) tool. It can (1) effectively process large data, (2) rapidly evaluate population structure, (3) efficiently estimate variance components several algorithms, (4) implement parallel-accelerated association tests of markers three methods, (5) globally efficient design on GWAS process computing, (6) enhance visualization of related information. rMVP contains three models GLM (Alkes Price (2006) <DOI:10.1038/ng1847>), MLM (Jianming Yu (2006) <DOI:10.1038/ng1702>) and FarmCPU (Xiaolei Liu (2016) <doi:10.1371/journal.pgen.1005767>); variance components estimation methods EMMAX (Hyunmin Kang (2008) <DOI:10.1534/genetics.107.080101>;), FaSTLMM (method: Christoph Lippert (2011) <DOI:10.1038/nmeth.1681>, R implementation from GAPIT2': You Tang and Xiaolei Liu (2016) <DOI:10.1371/journal.pone.0107684> and SUPER': Qishan Wang and Feng Tian (2014) <DOI:10.1371/journal.pone.0107684>), and HE regression (Xiang Zhou (2017) <DOI:10.1214/17-AOAS1052>).

The ecocrop model estimates environmental suitability for plants using a limiting factor approach for plant growth following Hackett (1991) <doi:10.1007/BF00045728>. The implementation in this package is fast and flexible: it allows for the use of any (environmental) predictor variable. Predictors can be either static (for example, soil pH) or dynamic (for example, monthly precipitation).

This package provides a collection of randomization tests, data sets and examples. The current version focuses on five testing problems and their implementation in empirical work. First, it facilitates the empirical researcher to test for particular hypotheses, such as comparisons of means, medians, and variances from k populations using robust permutation tests, which asymptotic validity holds under very weak assumptions, while retaining the exact rejection probability in finite samples when the underlying distributions are identical. Second, the description and implementation of a permutation test for testing the continuity assumption of the baseline covariates in the sharp regression discontinuity design (RDD) as in Canay and Kamat (2018) <https://goo.gl/UZFqt7>. More specifically, it allows the user to select a set of covariates and test the aforementioned hypothesis using a permutation test based on the Cramer-von Misses test statistic. Graphical inspection of the empirical CDF and histograms for the variables of interest is also supported in the package. Third, it provides the practitioner with an effortless implementation of a permutation test based on the martingale decomposition of the empirical process for testing for heterogeneous treatment effects in the presence of an estimated nuisance parameter as in Chung and Olivares (2021) <doi:10.1016/j.jeconom.2020.09.015>. Fourth, this version considers the two-sample goodness-of-fit testing problem under covariate adaptive randomization and implements a permutation test based on a prepivoted Kolmogorov-Smirnov test statistic. Lastly, it implements an asymptotically valid permutation test based on the quantile process for the hypothesis of constant quantile treatment effects in the presence of an estimated nuisance parameter.