An assortment of helper functions for doing structural equation modeling, mainly by lavaan for now. Most of them are time-saving functions for common tasks in doing structural equation modeling and reading the output. This package is not for functions that implement advanced statistical procedures. It is a light-weight package for simple functions that do simple tasks conveniently, with as few dependencies as possible.

This package provides genome wide annotation for E coli strain K12, primarily based on mapping using Entrez Gene identifiers. Entrez Gene is National Center for Biotechnology Information (NCBI)’s database for gene-specific information. Entrez Gene maintains records from genomes which have been completely sequenced, which have an active research community to submit gene-specific information, or which are scheduled for intense sequence analysis.

This NGINX module provides streaming with the RTMP, DASH, and HLS protocols. It allows NGINX to accept incoming RTMP streams for recording or redistribution. It also supports on-demand streaming from a file on disk and pulling from an upstream RTMP stream. Remote control of the module is possible over HTTP.

This package provides actuarial tools and building blocks for analysing, modelling, refining, and validating insurance rating models. Designed to support common GLM-based pricing tasks and the translation of statistical model output into practical tariff structures. The package supports the construction of insurance tariff classes using a data-driven approach, based on the methodology of Antonio and Valdez (2012) <doi:10.1007/s10182-011-0152-7>.

This package provides methods for interpolating data in the Munsell color system following the ASTM D-1535 standard. Hues and chromas with decimal values can be interpolated and converted to/from the Munsell color system and CIE xyY, CIE XYZ, CIE Lab, CIE Luv, or RGB. Includes ISCC-NBS color block lookup. Based on the work by Paul Centore, "The Munsell and Kubelka-Munk Toolbox".

Radio Beam is a simple toolkit for reading beam information from FITS headers and manipulating beams. Some example applications include:

• Convolution and deconvolution

• Unit conversion (Jy to/from K)

• Handle sets of beams for spectral cubes with varying resolution between channels

• Find the smallest common beam from a set of beams

• Add the beam shape to a matplotlib plot

JLine is a Java library for handling console input. It is similar in functionality to BSD editline and GNU readline but with additional features that bring it in par with ZSH line editor. People familiar with the readline/editline capabilities for modern shells (such as bash and tcsh) will find most of the command editing features of JLine to be familiar.

This package includes the line reader.

An interface to container functionality in Microsoft's Azure cloud: <https://azure.microsoft.com/en-us/products/category/containers/>. Manage Azure Container Instance (ACI), Azure Container Registry (ACR) and Azure Kubernetes Service (AKS) resources, push and pull images, and deploy services. On the client side, lightweight shells to the docker', docker-compose', kubectl and helm commandline tools are provided. Part of the AzureR family of packages.

Network is a prevalent form of data structure in many fields. As an object of analysis, many distance or metric measures have been proposed to define the concept of similarity between two networks. We provide a number of distance measures for networks. See Jurman et al (2011) <doi:10.3233/978-1-60750-692-8-227> for an overview on spectral class of inter-graph distance measures.

This package provides a Bayesian framework for inferring influenza infection status from serial antibody measurements. Jointly estimates season-specific infection probabilities, antibody boosting and waning after infection, and baseline hemagglutination inhibition (HAI) titer distributions via Markov chain Monte Carlo (MCMC). Supports multi-season analysis and subgroup comparisons via a group_by interface. See Tsang et al. (2022) <doi:10.1038/s41467-022-29310-8> for methodological details.

This package provides a unified set of helper functions to access datasets from the Seattle Open Data platform <https://data.seattle.gov/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API. The package provides a consistent interface for discovering and downloading datasets from the Seattle Open Data Portal using human-readable dataset keys or official Socrata dataset identifiers.

MetaboCoreUtils defines metabolomics-related core functionality provided as low-level functions to allow a data structure-independent usage across various R packages. This includes functions to calculate between ion (adduct) and compound mass-to-charge ratios and masses or functions to work with chemical formulas. The package provides also a set of adduct definitions and information on some commercially available internal standard mixes commonly used in MS experiments.

This package lets you compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference. Details can be found in Arel-Bundock, Greifer, and Heiss (2024) <doi:10.18637/jss.v111.i09>.

This package provides classes to implement, analyze and plot cohort life tables for actuarial calculations. Birth-year dependent cohort mortality tables using a yearly trend to extrapolate from a base year are implemented, as well as period life table, cohort life tables using an age shift, and merged life tables. Additionally, several data sets from various countries are included to provide widely-used tables out of the box.

Easily use Blueprint', the popular React library from Palantir, in your Shiny app. Blueprint provides a rich set of UI components for creating visually appealing applications and is optimized for building complex, data-dense web interfaces. This package provides most components from the underlying library, as well as special wrappers for some components to make it easy to use them in R without writing JavaScript code.

User tools for working with The STOICH (Stoichiometric Traits of Organisms in their Chemical Habitats) Project database <https://snr-stoich.unl.edu/>. This package is designed to aid in data discovery, filtering, pairing water samples with organism samples, and merging data tables to assist users in preparing data for analyses. For additional examples see "Additional Examples" and the readme file at <https://github.com/STOICH-project/STOICH-utilities>.

The wolfSSL embedded SSL library (formerly CyaSSL) is an SSL/TLS library written in ANSI C and targeted for embedded, RTOS, and resource-constrained environments - primarily because of its small size, speed, and feature set. wolfSSL supports industry standards up to the current TLS 1.3 and DTLS 1.2, is up to 20 times smaller than OpenSSL, and offers progressive ciphers such as ChaCha20, Curve25519, NTRU, and Blake2b.

Efficient implementations of multiple exact and approximate methods as described in Hong (2013) <doi:10.1016/j.csda.2012.10.006>, Biscarri, Zhao & Brunner (2018) <doi:10.1016/j.csda.2018.01.007> and Zhang, Hong & Balakrishnan (2018) <doi:10.1080/00949655.2018.1440294> for computing the probability mass, cumulative distribution and quantile functions, as well as generating random numbers for both the ordinary and generalised Poisson binomial distribution.

Identifies, filters and exports sex linked markers using SNP (single nucleotide polymorphism) data. To install the other packages, we recommend to install the dartRverse package, that supports the installation of all packages in the dartRverse'. If you want understand the applied rational to identify sexlinked markers and/or want to cite dartR.sexlinked', you find the information by typing citation('dartR.sexlinked') in the console.

This package provides functions for modelling microbial inactivation under isothermal or dynamic conditions. The calculations are based on several mathematical models broadly used by the scientific community and industry. Functions enable to make predictions for cases where the kinetic parameters are known. It also implements functions for parameter estimation for isothermal and dynamic conditions. The model fitting capabilities include an Adaptive Monte Carlo method for a Bayesian approach to parameter estimation.

Estimate the parameters of multivariate endogenous switching and sample selection models using methods described in Newey (2009) <doi:10.1111/j.1368-423X.2008.00263.x>, E. Kossova, B. Potanin (2018) <https://ideas.repec.org/a/ris/apltrx/0346.html>, E. Kossova, L. Kupriianova, B. Potanin (2020) <https://ideas.repec.org/a/ris/apltrx/0391.html> and E. Kossova, B. Potanin (2022) <https://ideas.repec.org/a/ris/apltrx/0455.html>.

Extends the caret framework to support late fusion workflows, enabling users to train models independently across multiple data modalities and combine their predictions into a single meta-model. Designed for developers, data scientists, and biomedical researchers alike, caretMultimodal aims to make late fusion ensemble modelling as accessible and flexible as single-dataset workflows in caret'. Late fusion methods are based on Wolpert (1992) <doi:10.1016/S0893-6080(05)80023-1>.

Two-step and maximum likelihood estimation of Heckman-type sample selection models: standard sample selection models (Tobit-2), endogenous switching regression models (Tobit-5), sample selection models with binary dependent outcome variable, interval regression with sample selection (only ML estimation), and endogenous treatment effects models. These methods are described in the three vignettes that are included in this package and in econometric textbooks such as Greene (2011, Econometric Analysis, 7th edition, Pearson).

Enables deploying configuration file-based shiny apps with minimal programming for interactive exploration and analysis showcase of molecular expression data. For exploration, supports visualization of correlations between rows of an expression matrix and a table of observations, such as clinical measures, and comparison of changes in expression over time. For showcase, enables visualizing the results of differential expression from package such as limma', co-expression modules from WGCNA and lower dimensional projections.