This package provides tools for qPCR data analysis using Delta Ct and Delta Delta Ct methods, including t-test, Wilcoxon-test, ANOVA models, and publication-ready visualizations. The package supports multiple target, and multiple reference genes, and uses a calculation framework adopted from Ganger et al. (2017) <doi:10.1186/s12859-017-1949-5> and Taylor et al. (2019) <doi:10.1016/j.tibtech.2018.12.002>, covering both the Livak and Pfaffl methods.

This package provides tools to fit and simulate realizations from relational event models.

T (extent of the primary tumor), N (absence or presence and extent of regional lymph node metastasis) and M (absence or presence of distant metastasis) are three components to describe the anatomical tumor extent. TNM stage is important in treatment decision-making and outcome predicting. The existing oropharyngeal Cancer (OPC) TNM stages have not made distinction of the two sub sites of Human papillomavirus positive (HPV+) and Human papillomavirus negative (HPV-) diseases. We developed novel criteria to assess performance of the TNM stage grouping schemes based on parametric modeling adjusting on important clinical factors. These criteria evaluate the TNM stage grouping scheme in five different measures: hazard consistency, hazard discrimination, explained variation, likelihood difference, and balance. The methods are described in Xu, W., et al. (2015) <https://www.austinpublishinggroup.com/biometrics/fulltext/biometrics-v2-id1014.php>.

This package performs RNA emulation and active learning proposed by Heo and Sung (2025) <doi:10.1080/00401706.2024.2376173> for multi-fidelity computer experiments. The RNA emulator is particularly useful when the simulations with different fidelity level are nonlinearly correlated. The hyperparameters in the model are estimated by maximum likelihood estimation.

This package provides methods for multiway data analysis by means of Parafac and Tucker 3 models. Robust versions (Engelen and Hubert (2011) <doi:10.1016/j.aca.2011.04.043>) and versions for compositional data are also provided (Gallo (2015) <doi:10.1080/03610926.2013.798664>, Di Palma et al. (2018) <doi:10.1080/02664763.2017.1381669>). Several optimization methods alternative to ALS are available (Simonacci and Gallo (2019) <doi:10.1016/j.chemolab.2019.103822>, Simonacci and Gallo (2020) <doi:10.1007/s00500-019-04320-9>).

The goal of Rigma is to provide a user friendly client to the Figma API <https://www.figma.com/developers/api>. It uses the latest `httr2` for a stable interface with the REST API. More than 20 methods are provided to interact with Figma files, and teams. Get design data into R by reading published components and styles, converting and downloading images, getting access to the full Figma file as a hierarchical data structure, and much more. Enhance your creativity and streamline the application development by automating the extraction, transformation, and loading of design data to your applications and HTML documents.

Connection to the Redis (or Valkey') key/value store using the C-language client library hiredis (included as a fallback) with MsgPack encoding provided via RcppMsgPack headers. It now also includes the pub/sub functions from the rredis package.

Enhances the R Optimization Infrastructure ('ROI') package with the possibility to obtain multiple solutions for linear problems with binary variables. The main function is copied (with small modifications) from the relations package.

Scalable implementation of classification and regression forests, as described by Breiman (2001), <DOI:10.1023/A:1010933404324>.

This package provides a simple and efficient way to read data from Paradox database files (.db) directly into R as modern tibble data frames. It uses the underlying pxlib C library, to handle the low-level file format details and provides a clean, user-friendly R interface.

Conducts mediation analysis for structural equation models (SEM) estimated with lavaan', blavaan', cSEM', or modsem'. Implements the Baron and Kenny (1986) <doi:10.1037/0022-3514.51.6.1173> and Zhao, Lynch & Chen (2010) <doi:10.1086/651257> approaches to determine the presence and type of mediation. Supports covariance-based SEM, partial least squares SEM, Bayesian SEM, and moderated mediation models. Reports indirect effects with standard errors from Sobel, Delta, Monte-Carlo, and bootstrap methods, along with effect size measures (RIT, RID).

This package provides read and write support for the Conic Benchmark Format (CBF, version 4) within the R Optimization Infrastructure ('ROI'). Supported cone types include the positive orthant, second-order (SOC), rotated second-order (bridged automatically to standard SOC), exponential (primal and dual), power (primal and dual), and semidefinite (symmetric-vectorised) cones, as well as their mixed-integer variants. The reader translates a .cbf file into an ROI OP object, handling coordinate-convention differences between CBF and ROI transparently; the writer serialises an ROI OP object back to CBF plain-text.

An interface to the Open Tree of Life API to retrieve phylogenetic trees, information about studies used to assemble the synthetic tree, and utilities to match taxonomic names to Open Tree identifiers'. The Open Tree of Life aims at assembling a comprehensive phylogenetic tree for all named species.

This package provides functions to assist in performing probabilistic record linkage and deduplication: generating pairs, comparing records, em-algorithm for estimating m- and u-probabilities (I. Fellegi & A. Sunter (1969) <doi:10.1080/01621459.1969.10501049>, T.N. Herzog, F.J. Scheuren, & W.E. Winkler (2007), "Data Quality and Record Linkage Techniques", ISBN:978-0-387-69502-0), forcing one-to-one matching. Can also be used for pre- and post-processing for machine learning methods for record linkage. Focus is on memory, CPU performance and flexibility.

An implementation of the RainFARM (Rainfall Filtered Autoregressive Model) stochastic precipitation downscaling method (Rebora et al. (2006) <doi:10.1175/JHM517.1>). Adapted for climate downscaling according to D'Onofrio et al. (2018) <doi:10.1175/JHM-D-13-096.1> and for complex topography as in Terzago et al. (2018) <doi:10.5194/nhess-18-2825-2018>. The RainFARM method is based on the extrapolation to small scales of the Fourier spectrum of a large-scale precipitation field, using a fixed logarithmic slope and random phases at small scales, followed by a nonlinear transformation of the resulting linearly correlated stochastic field. RainFARM allows to generate ensembles of spatially downscaled precipitation fields which conserve precipitation at large scales and whose statistical properties are consistent with the small-scale statistics of observed precipitation, based only on knowledge of the large-scale precipitation field.

Robust methods for estimating the parameters of multivariate Gaussian linear models.

Solve some conic related problems (intersection of conics with lines and conics, arc length of an ellipse, polar lines, etc.).

This package provides functions for connecting to BioUML server, querying BioUML repository and launching BioUML analyses.

Recursive display of names and paths of all the items nested within sublists of a list object.

This package provides tools for preprocessing and processing canopy photographs with support for raw data reading. Provides methods to address variability in sky brightness and to mitigate errors from image acquisition in non-diffuse light. Works with all types of fish-eye lenses, and some methods also apply to conventional lenses.

This package provides a methodology to perform multivariate measurement error adjustment using external validation data. Allows users to remove the attenuating effect of measurement error by incorporating a distribution of external validation data, and allows for plotting of all resultant adjustments. Sensitivity analyses can also be run through this package to test how different ranges of validity coefficients can impact the effect of the measurement error adjustment. The methods implemented in this package are based on the work by Muoka, A., Agogo, G., Ngesa, O., Mwambi, H. (2020): <doi:10.12688/f1000research.27892.1>.

Estimation of abundance and other demographic parameters for closed populations, open populations and the robust design in capture-recapture experiments using loglinear models.

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.

It provides external jars required for the rjdverse (as rjd3toolkit', rjd3x13 and rjd3tramoseats').