Optimize one or two-arm, two-stage designs for clinical trials with respect to several implemented objective criteria or custom objectives. Optimization under uncertainty and conditional (given stage-one outcome) constraints are supported. See Pilz et al. (2019) <doi:10.1002/sim.8291> and Kunzmann et al. (2021) <doi:10.18637/jss.v098.i09> for details.

The meaning of adea is "alternate DEA". This package is devoted to provide the alternative method of DEA described in the paper entitled "Stepwise Selection of Variables in DEA Using Contribution Load", by F. Fernandez-Palacin, M. A. Lopez-Sanchez and M. Munoz-Marquez. Pesquisa Operacional 38 (1), pg. 1-24, 2018. <doi:10.1590/0101-7438.2018.038.01.0031>. A full functional on-line and interactive version is available at <https://knuth.uca.es/shiny/DEA/>.

Computationally efficient method to estimate orthant probabilities of high-dimensional Gaussian vectors. Further implements a function to compute conservative estimates of excursion sets under Gaussian random field priors.

Flexible parametric Accelerated Hazards (AH) regression models in overall and relative survival frameworks with 13 distinct Baseline Distributions. The AH Model can also be applied to lifetime data with crossed survival curves. Any user-defined parametric distribution can be fitted, given at least an R function defining the cumulative hazard and hazard rate functions. See Chen and Wang (2000) <doi:10.1080/01621459.2000.10474236>, and Lee (2015) <doi:10.1007/s10985-015-9349-5> for more details.

Edit an Antares simulation before running it : create new areas, links, thermal clusters or binding constraints or edit existing ones. Update Antares general & optimization settings. Antares is an open source power system generator, more information available here : <https://antares-simulator.org/>.

Miscellaneous astronomy functions, utilities, and data.

Package for the access and distribution of long-term lake datasets from lakes in the Adirondack Park, northern New York state. Includes a wide variety of physical, chemical, and biological parameters from 28 lakes. Data are from multiple collection organizations and have been harmonized in both time and space for ease of reuse.

Accelerated destructive degradation tests (ADDT) are often used to collect necessary data for assessing the long-term properties of polymeric materials. Based on the collected data, a thermal index (TI) is estimated. The TI can be useful for material rating and comparison. This package implements the traditional method based on the least-squares method, the parametric method based on maximum likelihood estimation, and the semiparametric method based on spline methods, and the corresponding methods for estimating TI for polymeric materials. The traditional approach is a two-step approach that is currently used in industrial standards, while the parametric method is widely used in the statistical literature. The semiparametric method is newly developed. Both the parametric and semiparametric approaches allow one to do statistical inference such as quantifying uncertainties in estimation, hypothesis testing, and predictions. Publicly available datasets are provided illustrations. More details can be found in Jin et al. (2017).

EM algorithm for estimation of parameters and other methods in a quantile regression.

Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components, plus optionality for structural interpolation, using the Kalman filter. Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models" <doi:10.1093/oxfordhb/9780195398649.013.0006>. Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.

We provide tools to estimate two prediction accuracy metrics, the average positive predictive values (AP) as well as the well-known AUC (the area under the receiver operator characteristic curve) for risk scores. The outcome of interest is either binary or censored event time. Note that for censored event time, our functions estimates, the AP and the AUC, are time-dependent for pre-specified time interval(s). A function that compares the APs of two risk scores/markers is also included. Optional outputs include positive predictive values and true positive fractions at the specified marker cut-off values, and a plot of the time-dependent AP versus time (available for event time data).

An R console utility that lets you ask R related questions to the OpenAI large language model. It can answer how-to questions by providing code, and what-is questions by explaining what given code does. You must provision your own key for the OpenAI API <https://platform.openai.com/docs/api-reference>.

This package provides a chat package connecting to API endpoints by OpenAI (<https://platform.openai.com/>) to answer questions (about R).

Bland-Altman plot and scatter plot with identity line for visualization and point and interval estimates for different metrics related to reproducibility/repeatability/agreement including the concordance correlation coefficient, intraclass correlation coefficient, within-subject coefficient of variation, smallest detectable difference, and mean normalized smallest detectable difference.

This package provides a routine to partial out factors with many levels during the optimization of the log-likelihood function of the corresponding generalized linear model (glm). The package is based on the algorithm described in Stammann (2018) <doi:10.48550/arXiv.1707.01815> and is restricted to glm's that are based on maximum likelihood estimation and nonlinear. It also offers an efficient algorithm to recover estimates of the fixed effects in a post-estimation routine and includes robust and multi-way clustered standard errors. Further the package provides analytical bias corrections for binary choice models derived by Fernandez-Val and Weidner (2016) <doi:10.1016/j.jeconom.2015.12.014> and Hinz, Stammann, and Wanner (2020) <doi:10.48550/arXiv.2004.12655>.

Facilitates access to the data from the Atlas do Estado Brasileiro (<https://www.ipea.gov.br/atlasestado/>), maintained by the Instituto de Pesquisa Econômica Aplicada (Ipea). It allows users to search for specific series, list series or themes, and download data when available.

This package provides a few functions and several data set for the Springer book Applied Predictive Modeling'.

This package provides a collection of functions to compute frequently used metrics for nutrition trials in aquaculture. Implementations include metrics to calculate growth, feed conversion, nutrient use efficiency, and feed digestibility. The package supports reproducible workflows for summarising experimental results and reduces manual calculation errors. For additional information see Machado e Silva, Karthikeyan and Tellbüscher (2025) <doi:10.13140/RG.2.2.27322.04808>.

We propose an age-dependent topic modelling (ATM) model, providing a low-rank representation of longitudinal records of hundreds of distinct diseases in large electronic health record data sets. The model assigns to each individual topic weights for several disease topics; each disease topic reflects a set of diseases that tend to co-occur as a function of age, quantified by age-dependent topic loadings for each disease. The model assumes that for each disease diagnosis, a topic is sampled based on the individualâ s topic weights (which sum to 1 across topics, for a given individual), and a disease is sampled based on the individualâ s age and the age-dependent topic loadings (which sum to 1 across diseases, for a given topic at a given age). The model generalises the Latent Dirichlet Allocation (LDA) model by allowing topic loadings for each topic to vary with age. References: Jiang (2023) <doi:10.1038/s41588-023-01522-8>.

Considering an (n x m) data matrix X, this package is based on the method proposed by Gower, Groener, and Velden (2010) <doi:10.1198/jcgs.2010.07134>, and utilize the resulting matrices from the extended version of the NIPALS decomposition to determine n triangles whose areas are used to visually estimate the elements of a specific column of X. After a 90-degree rotation of the sample points, the triangles are drawn regarding the following points: 1.the origin of the axes; 2.the sample points; 3. the vector endpoint representing some variable.

This package implements the Classification-based on Association Rules (CBA) algorithm for association rule classification. The package, also described in Hahsler et al. (2019) <doi:10.32614/RJ-2019-048>, contains several convenience methods that allow to automatically set CBA parameters (minimum confidence, minimum support) and it also natively handles numeric attributes by integrating a pre-discretization step. The rule generation phase is handled by the arules package. To further decrease the size of the CBA models produced by the arc package, postprocessing by the qCBA package is suggested.

This package provides functions and data to accompany the 5th edition of the book "Applied Nonparametric Statistical Methods" (4th edition: Sprent & Smeeton, 2024, ISBN:158488701X), the revisions from the 4th edition including a move from describing the output from a miscellany of statistical software packages to using R. While the output from many of the functions can also be obtained using a range of other R functions, this package provides functions in a unified setting and give output using both p-values and confidence intervals, exemplifying the book's approach of treating p-values as a guide to statistical importance and not an end product in their own right. Please note that in creating the ANSM5 package we do not claim to have produced software which is necessarily the most computationally efficient nor the most comprehensive.

Estimates the attributable fraction in different sampling designs adjusted for measured confounders using logistic regression (cross-sectional and case-control designs), conditional logistic regression (matched case-control design), Cox proportional hazard regression (cohort design with time-to- event outcome), gamma-frailty model with a Weibull baseline hazard and instrumental variables analysis. An exploration of the AF with a genetic exposure can be found in the package AFheritability Dahlqwist E et al. (2019) <doi:10.1007/s00439-019-02006-8>.

This package provides Azure Active Directory (AAD) authentication functionality for R users of Microsoft's Azure cloud <https://azure.microsoft.com/en-us>. Use this package to obtain OAuth 2.0 tokens for services including Azure Resource Manager, Azure Storage and others. It supports both AAD v1.0 and v2.0, as well as multiple authentication methods, including device code and resource owner grant. Tokens are cached in a user-specific directory obtained using the rappdirs package. The interface is based on the OAuth framework in the httr package, but customised and streamlined for Azure. Part of the AzureR family of packages.