This package implements the algorithms for solving sparse generalized eigenvalue problem by Tan, et. al. (2018). Sparse Generalized Eigenvalue Problem: Optimal Statistical Rates via Truncated Rayleigh Flow. To appear in Journal of the Royal Statistical Society: Series B. <arXiv:1604.08697>.

Radiomics image analysis toolbox for 2D and 3D radiological images. RIA supports DICOM, NIfTI, nrrd and npy (numpy array) file formats. RIA calculates first-order, gray level co-occurrence matrix, gray level run length matrix and geometry-based statistics. Almost all calculations are done using vectorized formulas to optimize run speeds. Calculation of several thousands of parameters only takes minutes on a single core of a conventional PC. Detailed methodology has been published: Kolossvary et al. Circ: Cardiovascular Imaging. 2017;10(12):e006843 <doi: 10.1161/CIRCIMAGING.117.006843>.

This package provides a collection of several utility functions related to resolvable and affine resolvable Partially Balanced Incomplete Block Designs (PBIBDs), have been developed. In the class of resolvable designs, affine resolvable designs are said to be optimal, Bailey (1995) <doi:10.2307/2337638>. Here, the package contains three functions to generate and study the characterization properties of these designs. Developed functions are named as PBIBD1(), PBIBD2() and PBIBD3(), in which first two functions are used to generate two new series of affine resolvable PBIBDs and last one is used to generate a new series of resolvable PBIBDs, respectively. In addition, these functions can also be used to generate design parameters (v, b, r and k), canonical efficiency factors, variance factor between associates and average variance factors of the generated designs. Here v is the number of treatments, b (= b1 + b2, in case of non-proper design) is the number of blocks, r is the number of replications and k (= k1 + k2; k1 is the size of b1 and k2 is the size of b2) is the block size.

Create interactive radar charts using the Chart.js JavaScript library and the htmlwidgets package. Chart.js <http://www.chartjs.org/> is a lightweight library that supports several types of simple chart using the HTML5 canvas element. This package provides an R interface specifically to the radar chart, sometimes called a spider chart, for visualising multivariate data.

Focused on (but not exclusive to) data sets hosted on PhysioNet (<https://physionet.org>), ricu provides utilities for download, setup and access of intensive care unit (ICU) data sets. In addition to functions for running arbitrary queries against available data sets, a system for defining clinical concepts and encoding their representations in tabular ICU data is presented.

Takes matched and unmatched data and calculates Rosenbaum bounds for the treatment effect. Calculates bounds for binary outcome data, Hodges-Lehmann point estimates, Wilcoxon signed-rank test for matched data and matched IV estimators, Wilcoxon sum rank test, and for data with multiple matched controls. The sensitivity analysis methods in this package are documented in Rosenbaum (2002) Observational Studies, <doi:10.1007/978-1-4757-3692-2>, Springer-Verlag.

Facilitating the creation of reproducible statistical report templates. Once created, rapport templates can be exported to various external formats (HTML, LaTeX, PDF, ODT etc.) with pandoc as the converter backend.

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 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>.

The Snell scoring procedure, implemented in R. This procedure was first described by E.J Snell (1964) <doi:10.2307/2528498> and was later used by Tong et al (1977) <doi:10.4141/cjas77-001> in dairy.

Focused on linear, quadratic and cubic regression models, it has a function for calculating the models, obtaining a list with their parameters, and a function for making the graphs for the respective models.

Add-in to the RJDemetra package on seasonal adjustments. It allows to produce dashboards to summarise models and quickly check the quality of the seasonal adjustment.

In order to make sure that web request ends up in the correct handler function a router is often used. routr is a package implementing a simple but powerful routing functionality for R based servers. It is a fully functional fiery plugin, but can also be used with other httpuv based servers.

This package contains functions to interface with variables and variable details sheets, including recoding variables and converting them to PMML.

Interface to easily access data via the United States Department of Agriculture (USDA)'s Agricultural Resource Management Survey (ARMS) Data API <https://www.ers.usda.gov/developer/data-apis/arms-data-api/>. The downloaded data can be saved for later off-line use. Also provide relevant information and metadata for each of the input variables needed for sending the data inquery.

Supports concordances in R Markdown documents. This currently allows the original source location in the .Rmd file of errors detected by HTML tidy to be found more easily, and potentially allows forward and reverse search in HTML and LaTeX documents produced from R Markdown'. The LaTeX support has been included in the most recent development version of the patchDVI package.

Allows wrapping values in success() and failure() types to capture the result of operations, along with any status codes. Risky expressions can be wrapped in as_result() and functions wrapped in result() to catch errors and assign the relevant result types. Monadic functions can be bound together as pipelines or transaction scripts using then_try(), to gracefully handle errors at any step.

Adds menu items to the R Commander for implementing case 1 (object case) best-worst scaling (BWS1) from designing choice sets to measuring preferences for items. BWS1 is a question-based survey method that constructs various combinations of items (choice sets) using the experimental designs, asks respondents to select the best and worst items in each choice set, and then measures preferences for the items by analyzing the responses. For details, refer to Aizaki and Fogarty (2023) <doi:10.1016/j.jocm.2022.100394>.

Create production-ready Rich Text Format (RTF) tables and figures with flexible format.

This package produces tables with the level of replication (number of replicates) and the experimental uncoded values of the quantitative factors to be used for rotatable Central Composite Design (CCD) experimentation and a 2-D contour plot of the corresponding variance of the predicted response according to Mead et al. (2012) <doi:10.1017/CBO9781139020879> design_ccd(), and analyzes CCD data with response surface methodology ccd_analysis(). A rotatable CCD provides values of the variance of the predicted response that are concentrically distributed around the average treatment combination used in the experimentation, which with uniform precision (implied by the use of several replicates at the average treatment combination) improves greatly the search and finding of an optimum response. These properties of a rotatable CCD represent undeniable advantages over the classical factorial design, as discussed by Panneton et al. (1999) <doi:10.13031/2013.13267> and Mead et al. (2012) <doi:10.1017/CBO9781139020879.018> among others.

This package contains example data for the rehh package.

Various functions for querying and reshaping dependency trees, as for instance created with the spacyr or udpipe packages. This enables the automatic extraction of useful semantic relations from texts, such as quotes (who said what) and clauses (who did what). Method proposed in Van Atteveldt et al. (2017) <doi:10.1017/pan.2016.12>.

This package provides a lightweight implementation of the geomorphon terrain form classification algorithm of Jasiewicz and Stepinski (2013) <doi:10.1016/j.geomorph.2012.11.005> based largely on the GRASS GIS r.geomorphon module. This implementation employs a novel algorithm written in C++ and RcppParallel'.

Quickly install Java Development Kit (JDK) without administrative privileges and set environment variables in current R session or project to solve common issues with Java environment management in R'. Recommended to users of Java'/'rJava'-dependent R packages such as r5r', opentripplanner', xlsx', openNLP', rWeka', RJDBC', tabulapdf', and many more. rJavaEnv prevents common problems like Java not found, Java version conflicts, missing Java installations, and the inability to install Java due to lack of administrative privileges. rJavaEnv automates the download, installation, and setup of the Java on a per-project basis by setting the relevant JAVA_HOME in the current R session or the current working directory (via .Rprofile', with the user's consent). Similar to what renv does for R packages, rJavaEnv allows different Java versions to be used across different projects, but can also be configured to allow multiple versions within the same project (e.g. with the help of targets package). Note: there are a few extra steps for Linux users, who don't have any Java previously installed in their system, and who prefer package installation from source, rather then installing binaries from Posit Package Manager'. See documentation for details.