This package provides a collection of (wrapper) functions the creator found useful for quickly placing data summaries and formatted regression results into .Rnw or .Rmd files. Functions for generating commonly used graphics, such as receiver operating curves or Bland-Altman plots, are also provided by qwraps2'. qwraps2 is an updated version of a package qwraps'. The original version qwraps was never submitted to CRAN but can be found at <https://github.com/dewittpe/qwraps/>. The implementation and limited scope of the functions within qwraps2 <https://github.com/dewittpe/qwraps2/> is fundamentally different from qwraps'.

This package provides functions for estimating ploidy levels and detecting aneuploidy in individuals using allele intensities or allele count data from high-throughput genotyping platforms, including single nucleotide polymorphism (SNP) arrays and sequencing-based technologies. Implements method described in Taniguti et al. (2025) <doi:10.1002/tpg2.70044> an extended version of the PennCNV signal standardization method by Wang et al. (2007) <doi:10.1101/gr.6861907> for higher ploidy levels. Computes B-allele frequencies (BAF), z-scores, and identifies copy number variation patterns.

Functionality to read, recode, and transcode data as used in quantitative language comparison, specifically to deal with multilingual orthographic variation (Moran & Cysouw (2018) <doi:10.5281/zenodo.1296780>) and with the recoding of nominal data.

Qiita is a technical knowledge sharing and collaboration platform for programmers. See <https://qiita.com/api/v2/docs> for more information.

This package provides tools for an automated identification of diagnostic molecular characters, i.e. such columns in a given nucleotide or amino acid alignment that allow to distinguish taxa from each other. These characters can then be used to complement the formal descriptions of the taxa, which are often based on morphological and anatomical features. Especially for morphologically cryptic species, this will be helpful. QUIDDICH distinguishes between four different types of diagnostic characters. For more information, see "Kuehn, A.L., Haase, M. 2019. QUIDDICH: QUick IDentification of DIagnostic CHaracters.".

An extensive set of functions to perform Qualitative Comparative Analysis: crisp sets ('csQCA'), temporal ('tQCA'), multi-value ('mvQCA') and fuzzy sets ('fsQCA'). QCA is a methodology that bridges the qualitative and quantitative divide in social science research. It uses a Boolean minimization algorithm, resulting in a minimal causal configuration associated with a given phenomenon.

Enables the user to calculate Value at Risk (VaR) and Expected Shortfall (ES) by means of various types of historical simulation. Currently plain-, age-, volatility-weighted- and filtered historical simulation are implemented in this package. Volatility weighting can be carried out via an exponentially weighted moving average model (EWMA) or other GARCH-type models. The performance can be assessed via Traffic Light Test, Coverage Tests and Loss Functions. The methods of the package are described in Gurrola-Perez, P. and Murphy, D. (2015) <https://EconPapers.repec.org/RePEc:boe:boeewp:0525> as well as McNeil, J., Frey, R., and Embrechts, P. (2015) <https://ideas.repec.org/b/pup/pbooks/10496.html>.

Resources, tutorials, and code snippets dedicated to exploring the intersection of quantum computing and artificial intelligence (AI) in the context of analyzing Cluster of Differentiation 4 (CD4) lymphocytes and optimizing antiretroviral therapy (ART) for human immunodeficiency virus (HIV). With the emergence of quantum artificial intelligence and the development of small-scale quantum computers, there's an unprecedented opportunity to revolutionize the understanding of HIV dynamics and treatment strategies. This project leverages a quantum computer simulator, to explore these applications in quantum computing techniques, addressing the challenges in studying CD4 lymphocytes and enhancing ART efficacy.

This R package assists breeders in linking data systems with their analytic pipelines, a crucial step in digitizing breeding processes. It supports querying and retrieving phenotypic and genotypic data from systems like EBS <https://ebs.excellenceinbreeding.org/>, BMS <https://bmspro.io>, BreedBase <https://breedbase.org>, GIGWA <https://github.com/SouthGreenPlatform/Gigwa2> (using BrAPI <https://brapi.org> calls), , and Germinate <https://germinateplatform.github.io/get-germinate/>. Extra helper functions support environmental data sources, including TerraClimate <https://www.climatologylab.org/terraclimate.html> and FAO HWSDv2 <https://gaez.fao.org/pages/hwsd> soil database.

PKG_DESC.

Values different types of assets and calibrates discount curves for quantitative financial analysis. It covers fixed coupon assets, floating note assets, interest and cross currency swaps with different payment frequencies. Enables the calibration of spot, instantaneous forward and basis curves, making it a powerful tool for accurate and flexible bond valuation and curve generation. The valuation and calibration techniques presented here are consistent with industry standards and incorporates author's own calculations. Tuckman, B., Serrat, A. (2022, ISBN: 978-1-119-83555-4).

Simplifies output suppression logic in R packages, as it's common to develop some form of it in R. quietR intends to simplify that problem and allow a set of simple toggle functions to be used to suppress console output.

Quasi-Cauchy quantile regression, proposed by de Oliveira, Ospina, Leiva, Figueroa-Zuniga and Castro (2023) <doi:10.3390/fractalfract7090667>. This regression model is useful for the case where you want to model data of a nature limited to the intervals [0,1], (0,1], [0,1) or (0,1) and you want to use a quantile approach.

QuantLib bindings are provided for R using Rcpp via an evolved version of the initial header-only Quantuccia project offering an subset of QuantLib (now maintained separately just for the calendaring subset). See the included file AUTHORS for a full list of contributors to QuantLib (and hence also Quantuccia').

Manages, builds and computes statistics and datasets for the construction of quarterly (sub-annual) life tables by exploiting micro-data from either a general or an insured population. References: Pavà a and Lledó (2022) <doi:10.1111/rssa.12769>. Pavà a and Lledó (2023) <doi:10.1017/asb.2023.16>. Pavà a and Lledó (2025) <doi:10.1371/journal.pone.0315937>. Acknowledgements: The authors wish to thank Conselleria de Educación, Universidades y Empleo, Generalitat Valenciana (grants AICO/2021/257; CIAICO/2024/031), Ministerio de Ciencia e Innovación (grant PID2021-128228NB-I00) and Fundación Mapfre (grant Modelización espacial e intra-anual de la mortalidad en España. Una herramienta automática para el calculo de productos de vida') for supporting this research.

Grows a qualitative interaction tree. Quint is a tool for subgroup analysis, suitable for data from a two-arm randomized controlled trial. More information in Dusseldorp, E., Doove, L., & Van Mechelen, I. (2016) <doi:10.3758/s13428-015-0594-z>.

This package provides convenience utilities for using DuckDB directly over datasets stored in Azure Data Lake Storage Gen2 (ADLS Gen2, abfss://'). Opens connections configured for Azure-backed Delta Lake and Parquet data, registers Azure credentials as DuckDB secrets, and supports optional repository mirrors for restricted networks. Integrates well with DBI for SQL workflows and with dplyr and dbplyr for lazy table queries.

To construct a model in 2-D space from 2-D nonlinear dimension reduction data and then lift it to the high-dimensional space. Additionally, provides tools to visualise the model overlay the data in 2-D and high-dimensional space. Furthermore, provides summaries and diagnostics to evaluate the nonlinear dimension reduction layout.

Quantile regression (QR) for Nonlinear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference result is for the fixed-effects and variance components. It also provides prediction and graphical summaries for assessing the algorithm convergence and fitting results.

Quickly fits and plots psychometric functions (normal, logistic, Weibull or any or any function defined by the user) for multiple groups.

The computation of quadratic form (QF) distributions is often not trivial and it requires numerical routines. The package contains functions aimed at evaluating the exact distribution of quadratic forms (QFs) and ratios of QFs. In particular, we propose to evaluate density, quantile and distribution functions of positive definite QFs and ratio of independent positive QFs by means of an algorithm based on the numerical inversion of Mellin transforms.

Provide access to QUANTkiosk platform of regulatory and corporate data relevant to financial markets including point-in-time fundamentals, ownership and symbology.

This package provides functions for the joint analysis of Q sets of p-values obtained for the same list of items. This joint analysis is performed by querying a composite hypothesis, i.e. an arbitrary complex combination of simple hypotheses, as described in Mary-Huard et al. (2021) <doi:10.1093/bioinformatics/btab592> and De Walsche et al.(2025) <doi: 10.1093/nargab/lqaf118>. In this approach, the Q-uplet of p-values associated with each item is distributed as a multivariate mixture, where each of the 2^Q components corresponds to a specific combination of simple hypotheses. The dependence between the p-value series is considered using a Gaussian copula function. A p-value for the composite hypothesis test is derived from the posterior probabilities.

This package provides tools for (automated and manual) quality control of the results of Epigenome-Wide Association Studies.