The real-time quantitative polymerase chain reaction (qPCR) technical data sets by Ruijter et al. (2013) <doi:10.1016/j.ymeth.2012.08.011>: (i) the four-point 10-fold dilution series; (ii) 380 replicates; and (iii) the competimer data set. These three data sets can be used to benchmark qPCR methods. Original data set is available at <https://medischebiologie.nl/wp-content/uploads/2019/02/qpcrdatamethods.zip>. This package fixes incorrect annotations in the original data sets.

Retrieves efficiently and reliably Investors Exchange ('IEX') stock and market data using IEX Cloud API'. The platform is offered by Investors Exchange Group (IEX Group). Main goal is to leverage R capabilities including existing packages to effectively provide financial and statistical analysis as well as visualization in support of fact-based decisions. In addition, continuously improve and enhance Riex by applying best practices and being in tune with users feedback and requirements. Please, make sure to review and acknowledge Investors Exchange Group (IEX Group) terms and conditions before using Riex (<https://iexcloud.io/terms/>).

This is a analysis toolkit to streamline the analyses of minicircle sequence diversity in population-scale genome projects. rKOMICS is a user-friendly R package that has simple installation requirements and that is applicable to all 27 trypanosomatid genera. Once minicircle sequence alignments are generated, rKOMICS allows to examine, summarize and visualize minicircle sequence diversity within and between samples through the analyses of minicircle sequence clusters. We showcase the functionalities of the (r)KOMICS tool suite using a whole-genome sequencing dataset from a recently published study on the history of diversification of the Leishmania braziliensis species complex in Peru. Analyses of population diversity and structure highlighted differences in minicircle sequence richness and composition between Leishmania subspecies, and between subpopulations within subspecies. The rKOMICS package establishes a critical framework to manipulate, explore and extract biologically relevant information from mitochondrial minicircle assemblies in tens to hundreds of samples simultaneously and efficiently. This should facilitate research that aims to develop new molecular markers for identifying species-specific minicircles, or to study the ancestry of parasites for complementary insights into their evolutionary history. ***** !! WARNING: this package relies on dependencies from Bioconductor. For Mac users, this can generate errors when installing rKOMICS. Install Bioconductor and ComplexHeatmap at advance: install.packages("BiocManager"); BiocManager::install("ComplexHeatmap") *****.

The minimal rrapply'-package contains a single function rrapply(), providing an extended implementation of R'-base rapply() by allowing to recursively apply a function to elements of a nested list based on a general condition function and including the possibility to prune or aggregate nested list elements from the result. In addition, special arguments can be supplied to access the name, location, parents and siblings in the nested list of the element under evaluation. The rrapply() function builds upon rapply()'s native C implementation and requires no other package dependencies.

This package provides the datasets in the book "Methods of Multivariate Analysis (3rd)", such as Table 6.27 Blood Pressure Data, for statistical analysis,especially MANOVA. The dataset names correspond to their numbering in the third edition of the book, such as table6.27. Based on the book by Rencher and Christensen (2012, ISBN:9780470178966).

Standardized methods for calculating common important derived physical features of lakes including water density based based on temperature, thermal layers, thermocline depth, lake number, Wedderburn number, Schmidt stability and others.

Rogue ("wildcard") taxa are leaves with uncertain phylogenetic position. Their position may vary from tree to tree under inference methods that yield a tree set (e.g. bootstrapping, Bayesian tree searches, maximum parsimony). The presence of rogue taxa in a tree set can potentially remove all information from a consensus tree. The information content of a consensus tree - a function of its resolution and branch support values - can often be increased by removing rogue taxa. Rogue provides an explicitly information-theoretic approach to rogue detection (Smith 2022) <doi:10.1093/sysbio/syab099>, and an interface to RogueNaRok (Aberer et al. 2013) <doi:10.1093/sysbio/sys078>.

Implementation of the methods described in the paper with the above title: Langsrud, Ã . (2019) <doi:10.1007/s11222-018-9848-9>. The package can be used to generate synthetic or hybrid continuous microdata, and the relationship to the original data can be controlled in several ways. A function for replacing suppressed tabular cell frequencies with decimal numbers is included.

Decimal rounding is non-trivial in binary arithmetic. ISO standard round to even is more rare than typically assumed as most decimal fractions are not exactly representable in binary. Our roundX() versions explore differences between current and potential future versions of round() in R. Further, provides (some partly related) C99 math lib functions not in base R.

The header-only modern C++ template library Magic Enum for static reflection of enums (to string, from string, iteration) is provided by this package. More information about the underlying library can be found at its repository at <https://github.com/Neargye/magic_enum>.

Aims at loading Criteo online advertising campaign data into R. Criteo <http://www.criteo.com/> is an online advertising service that enables advertisers to display commercial ads to web users. The package provides an authentication process for R with the Criteo API <http://kb.criteo.com/ advertising/content/5/27/en/api.html>. Moreover, the package features an interface to query campaign data from the Criteo API. The data can be downloaded and will be transformed into a R data frame.

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>.

Wrapper for Datamuse API to find rhyming and other associated words. This includes words of similar meaning, spelling, or other related words. Learn more about the Datamuse API here <https://www.datamuse.com/api/>.

Bindings to kernel methods for enforcing security restrictions. AppArmor can apply mandatory access control (MAC) policies on a given task (process) via security profiles with detailed ACL definitions. In addition this package implements bindings for setting process resource limits (rlimit), uid, gid, affinity and priority. The high level R function eval.secure builds on these methods to perform dynamic sandboxing: it evaluates a single R expression within a temporary fork which acts as a sandbox by enforcing fine grained restrictions without affecting the main R process. A portable version of this function is now available in the unix package.

Indirect method for the estimation of reference intervals (RIs) using Real-World Data ('RWD') and methods for comparing and verifying RIs. Estimates RIs by applying advanced statistical methods to routine diagnostic test measurements, which include both pathological and non-pathological samples, to model the distribution of non-pathological samples. This distribution is then used to derive reference intervals and support RI verification, i.e., deciding if a specific RI is suitable for the local population. The package also provides functions for printing and plotting algorithm results. See ?refineR for a detailed description of features. Version 1.0 of the algorithm is described in Ammer et al. (2021) <doi:10.1038/s41598-021-95301-2>. Additional guidance is in Ammer et al. (2023) <doi:10.1093/jalm/jfac101>. The verification method is described in Beck et al. (2025) <doi:10.1515/cclm-2025-0728>.

Rcpp11 includes a header only C++11 library that facilitates integration between R and modern C++.

Parse scientific names using gnparser (<https://github.com/gnames/gnparser>), written in Go. gnparser parses scientific names into their component parts; it utilizes a Parsing Expression Grammar specifically for scientific names.

Random generation of survival data from a wide range of regression models, including accelerated failure time (AFT), proportional hazards (PH), proportional odds (PO), accelerated hazard (AH), Yang and Prentice (YP), and extended hazard (EH) models. The package rsurv also stands out by its ability to generate survival data from an unlimited number of baseline distributions provided that an implementation of the quantile function of the chosen baseline distribution is available in R. Another nice feature of the package rsurv lies in the fact that linear predictors are specified via a formula-based approach, facilitating the inclusion of categorical variables and interaction terms. The functions implemented in the package rsurv can also be employed to simulate survival data with more complex structures, such as survival data with different types of censoring mechanisms, survival data with cure fraction, survival data with random effects (frailties), multivariate survival data, and competing risks survival data. Details about the R package rsurv can be found in Demarqui (2024) <doi:10.48550/arXiv.2406.01750>.

The quantitative measurement and detection of molecules in HPLC should be carried out by an accurate description of chromatographic peaks. In this package non-linear fitting using a modified Gaussian model with a parabolic variance (PVMG) has been implemented to obtain the retention time and height at the peak maximum. This package also includes the traditional Van Deemter approach and two alternatives approaches to characterize chromatographic column.

Estimates and plots as a heat map the rolling window wavelet correlation (RWWC) coefficients statistically significant (within the 95% CI) between two regular (evenly spaced) time series. RolWinWavCor also plots at the same graphic the time series under study. The RolWinWavCor was designed for financial time series, but this software can be used with other kinds of data (e.g., climatic, ecological, geological, etc). The functions contained in RolWinWavCor are highly flexible since these contains some parameters to personalize the time series under analysis and the heat maps of the rolling window wavelet correlation coefficients. Moreover, we have also included a data set (named EU_stock_markets) that contains nine European stock market indices to exemplify the use of the functions contained in RolWinWavCor'. Methods derived from Polanco-Martà nez et al (2018) <doi:10.1016/j.physa.2017.08.065>).

Models and displays tephra transport through custom (windy, turbulent, heterogeneous) atmosphere over custom topography. Includes a Lagrangian (particle-tracking) tephra transport model and a function to save snapshots of model as png files.

Base S4-classes and functions for robust asymptotic statistics.

Manually bin data using weight of evidence and information value. Includes other binning methods such as equal length, quantile and winsorized. Options for combining levels of categorical data are also available. Dummy variables can be generated based on the bins created using any of the available binning methods. References: Siddiqi, N. (2006) <doi:10.1002/9781119201731.biblio>.

This package provides the user with functions to develop their trading strategy, uncover actionable trading ideas, and monitor consensus shifts with crowdsourced earnings and economic estimate data directly from <www.estimize.com>. Further information regarding the web services this package invokes can be found at <www.estimize.com/api>.