This package provides a simple interface to developing complex data pipelines which can be executed in a single call. sewage makes it easy to test, debug, and share data pipelines through it's interface and visualizations.

This package provides a comprehensive logging framework for R applications that provides hierarchical logging levels, database integration, and contextual logging capabilities. The package supports SQLite storage for persistent logs, provides colour-coded console output for better readability, includes parallel processing support, and implements structured error reporting with JSON formatting.

New tools for post-selection inference, for use with forward stepwise regression, least angle regression, the lasso, and the many means problem. The lasso function implements Gaussian, logistic and Cox survival models.

Artificial selection through selective breeding is an efficient way to induce changes in traits of interest in experimental populations. This package (sra) provides a set of tools to analyse artificial-selection response datasets. The data typically feature for several generations the average value of a trait in a population, the variance of the trait, the population size and the average value of the parents that were chosen to breed. Sra implements two families of models aiming at describing the dynamics of the genetic architecture of the trait during the selection response. The first family relies on purely descriptive (phenomenological) models, based on an autoregressive framework. The second family provides different mechanistic models, accounting e.g. for inbreeding, mutations, genetic and environmental canalization, or epistasis. The parameters underlying the dynamics of the time series are estimated by maximum likelihood. The sra package thus provides (i) a wrapper for the R functions mle() and optim() aiming at fitting in a convenient way a predetermined set of models, and (ii) some functions to plot and analyze the output of the models.

Sentiment Analysis via deep learning and gradient boosting models with a lot of the underlying hassle taken care of to make the process as simple as possible. In addition to out-performing traditional, lexicon-based sentiment analysis (see <https://benwiseman.github.io/sentiment.ai/#Benchmarks>), it also allows the user to create embedding vectors for text which can be used in other analyses. GPU acceleration is supported on Windows and Linux.

Simulation tools to evaluate the long-term effects of salmon management strategies, including a combination of habitat, harvest, and habitat actions. The stochastic age-structured operating model accommodates complex life histories, including freshwater survival across early life stages, juvenile survival and fishery exploitation in the marine life stage, partial maturity by age class, and fitness impacts of hatchery programs on natural spawning populations. salmonMSE also provides an age-structured conditioning model to develop operating models fitted to data.

This package provides a small set of functions wrapping up the call stack and command line inspection needed to determine a running script's filename from within the script itself.

Last.fm'<https://www.last.fm> is a music platform focussed on building a detailed profile of a users listening habits. It does this by scrobbling (recording) every track you listen to on other platforms ('spotify', youtube', soundcloud etc) and transferring them to your Last.fm database. This allows Last.fm to act as a complete record of your entire listening history. scrobbler provides helper functions to download and analyse your listening history in R.

This package provides tools for power and sample size calculation as well as design diagnostics for longitudinal mixed model settings, with a focus on stepped wedge designs. All calculations are oracle estimates i.e. assume random effect variances to be known (or guessed) in advance. The method is introduced in Hussey and Hughes (2007) <doi:10.1016/j.cct.2006.05.007>, extensions are discussed in Li et al. (2020) <doi:10.1177/0962280220932962>.

Full text, in data frames containing one row per verse, of the Standard Works of The Church of Jesus Christ of Latter-day Saints (LDS). These are the Old Testament, (KJV), the New Testament (KJV), the Book of Mormon, the Doctrine and Covenants, and the Pearl of Great Price.

This package provides a framework for modeling cellular metabolic states and continuous metabolic trajectories from single-cell RNA-seq data using pathway-level scoring. Enables lineage-restricted metabolic analysis, metabolic pseudotime inference, module-level trend analysis, and visualization of metabolic state transitions.

This package provides tools to simulate realistic raw case data for an epidemic in the form of line lists and contacts using a branching process. Simulated outbreaks are parameterised with epidemiological parameters and can have age-structured populations, age-stratified hospitalisation and death risk and time-varying case fatality risk.

This package performs multiple testing corrections that take specific structure of hypotheses into account, as described in Sankaran & Holmes (2014) <doi:10.18637/jss.v059.i13>.

Summary ellipses superimposed on a scatter plot contain all bi-variate summary statistics for regression analysis. Furthermore, the outer ellipse flags potential outliers. Multiple groups can be compared in terms of centers and spreads as illustrated in the examples.

You can easily add advanced cohort-building component to your analytical dashboard or simple Shiny app. Then you can instantly start building cohorts using multiple filters of different types, filtering datasets, and filtering steps. Filters can be complex and data-specific, and together with multiple filtering steps you can use complex filtering rules. The cohort-building sidebar panel allows you to easily work with filters, add and remove filtering steps. It helps you with handling missing values during filtering, and provides instant filtering feedback with filter feedback plots. The GUI panel is not only compatible with native shiny bookmarking, but also provides reproducible R code.

R client and utilities for Seven Bridges Platform API, from Cancer Genomics Cloud to other Seven Bridges supported platforms. API documentation is hosted publicly at <https://docs.sevenbridges.com/docs/the-api>.

This package provides digital tools for performing analyses within Social Dynamics and complexity in the Ancient Mediterranean (SDAM), which is a research group based at the Department of History and Classical Studies at Aarhus University.

These are tools that allow users to do time series diagnostics, primarily tests of unit root, by way of simulation. While there is nothing necessarily wrong with the received wisdom of critical values generated decades ago, simulation provides its own perks. Not only is simulation broadly informative as to what these various test statistics do and what are their plausible values, simulation provides more flexibility for assessing unit root by way of different thresholds or different hypothesized distributions.

Social risks are increasingly becoming a critical component of health care research. One of the most common ways to identify social needs is by using ICD-10-CM "Z-codes." This package identifies social risks using varying taxonomies of ICD-10-CM Z-codes from administrative health care data. The conceptual taxonomies come from: Centers for Medicare and Medicaid Services (2021) <https://www.cms.gov/files/document/zcodes-infographic.pdf>, Reidhead (2018) <https://web.mhanet.com/>, A Arons, S DeSilvey, C Fichtenberg, L Gottlieb (2018) <https://sirenetwork.ucsf.edu/tools-resources/resources/compendium-medical-terminology-codes-social-risk-factors>.

Data and functions to support Bayesian and frequentist inference and decision making for the Coursera Specialization "Statistics with R". See <https://github.com/StatsWithR/statsr> for more information.

Generates and evaluates D, I, A, Alias, E, T, and G optimal designs. Supports generation and evaluation of blocked and split/split-split/.../N-split plot designs. Includes parametric and Monte Carlo power evaluation functions, and supports calculating power for censored responses. Provides a framework to evaluate power using functions provided in other packages or written by the user. Includes a Shiny graphical user interface that displays the underlying code used to create and evaluate the design to improve ease-of-use and make analyses more reproducible. For details, see Morgan-Wall et al. (2021) <doi:10.18637/jss.v099.i01>.

This package provides functions to retrieve, process, analyze, and quality-control marine physical, chemical, and biological data. The main focus is on Swedish monitoring data available through the SHARK database <https://shark.smhi.se/en/>, with additional API support for Nordic Microalgae <https://nordicmicroalgae.org/>, Dyntaxa <https://artfakta.se/>, World Register of Marine Species ('WoRMS') <https://www.marinespecies.org>, AlgaeBase <https://www.algaebase.org>, OBIS xylookup web service <https://iobis.github.io/xylookup/> and Intergovernmental Oceanographic Commission (IOC) - UNESCO databases on harmful algae <https://www.marinespecies.org/hab/> and toxins <https://toxins.hais.ioc-unesco.org/>.

This package provides infrastructure functionalities such as missing value treatment, information value calculation, GINI calculation etc. which are used for developing a traditional credit scorecard as well as a machine learning based model. The functionalities defined are standard steps for any credit underwriting scorecard development, extensively used in financial domain.

Estimates the proportion of treatment effect on a censored primary outcome that is explained by the treatment effect on a censored surrogate outcome/event. All methods are described in detail in Parast, et al (2020) "Assessing the Value of a Censored Surrogate Outcome" <doi:10.1007/s10985-019-09473-1> and Wang et al (2025) "Model-free Approach to Evaluate a Censored Intermediate Outcome as a Surrogate for Overall Survival" <doi:10.1002/sim.70268>. A tutorial for this package can be found at <https://www.laylaparast.com/surrogateoutcome>.