This package implements the high-dimensional changepoint detection method GeomCP and the related mappings used for changepoint detection. These methods view the changepoint problem from a geometrical viewpoint and aim to extract relevant geometrical features in order to detect changepoints. The geomcp() function should be your first point of call. References: Grundy et al. (2020) <doi:10.1007/s11222-020-09940-y>.

Setup and connect to OpenTripPlanner (OTP) <http://www.opentripplanner.org/>. OTP is an open source platform for multi-modal and multi-agency journey planning written in Java'. The package allows you to manage a local version or connect to remote OTP server to find walking, cycling, driving, or transit routes. This package has been peer-reviewed by rOpenSci (v. 0.2.0.0).

Location- and scale-invariant Box-Cox and Yeo-Johnson power transformations allow for transforming variables with distributions distant from 0 to normality. Transformers are implemented as S4 objects. These allow for transforming new instances to normality after optimising fitting parameters on other data. A test for central normality allows for rejecting transformations that fail to produce a suitably normal distribution, independent of sample number.

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.

Clusters state sequences and weighted data. It provides an optimized weighted PAM algorithm as well as functions for aggregating replicated cases, computing cluster quality measures for a range of clustering solutions and plotting (fuzzy) clusters of state sequences. Parametric bootstraps methods to validate typology of sequences are also provided. Finally, it provides a fuzzy and crisp CLARA algorithm to cluster large database with sequence analysis.

This package provides a tool to search and download a collection of publicly available single cell ATAC-seq datasets and their metadata. scATAC-Explorer aims to act as a single point of entry for users looking to study single cell ATAC-seq data. Users can quickly search available datasets using the metadata table and download datasets of interest for immediate analysis within R.

This package provides functions for assessing variable relations and associations prior to modeling with a Random Forest algorithm (although these are relevant for any predictive model). Metrics such as partial correlations and variance inflation factors are tabulated as well as plotted for the user. A function is available for tuning the main Random Forest hyper-parameter based on model performance and variable importance metrics. This grid-search technique provides tables and plots showing the effect of the main hyper-parameter on each of the assessment metrics. It also returns each of the evaluated models to the user. The package also provides superior variable importance plots for individual models. All of the plots are developed so that the user has the ability to edit and improve further upon the plots. Derivations and methodology are described in Bladen (2022) <https://digitalcommons.usu.edu/etd/8587/>.

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".

In concurrent programming, sometimes it is desirable to make sure commonly accessed shared data is not all placed into the same cache line. Updating an atomic value invalides the whole cache line it belongs to, which makes the next access to the same cache line slower for other CPU cores. Use CachePadded to ensure updating one piece of data doesn't invalidate other cached data.

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.

The disparity filter algorithm is a network reduction technique to identify the backbone structure of a weighted network without destroying its multi-scale nature. The algorithm is documented in M. Angeles Serrano, Marian Boguna and Alessandro Vespignani in "Extracting the multiscale backbone of complex weighted networks", Proceedings of the National Academy of Sciences 106 (16), 2009. This implementation of the algorithm supports both directed and undirected networks.

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 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 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.

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.

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 generalized Poisson binomial distribution.

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.

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.

Means to predict process flow, such as process outcome, next activity, next time, remaining time, and remaining trace. Off-the-shelf predictive models based on the concept of Transformers are provided, as well as multiple ways to customize the models. This package is partly based on work described in Zaharah A. Bukhsh, Aaqib Saeed, & Remco M. Dijkman. (2021). "ProcessTransformer: Predictive Business Process Monitoring with Transformer Network" <arXiv:2104.00721>.

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>.