Convert general transit feed specification (GTFS) data to global positioning system (GPS) records in data.table format. It also has some functions to subset GTFS data in time and space and to convert both representations to simple feature format.
Access data on plant genetic resources from genebanks around the world published on Genesys (<https://www.genesys-pgr.org>). Your use of data is subject to terms and conditions available at <https://www.genesys-pgr.org/content/legal/terms>.
This package contains five functions performing the calculation of unconditional and conditional Granger-causality spectra, bootstrap inference on both, and inference on the difference between them via the bootstrap approach of Farne and Montanari, 2018 <arXiv:1803.00374>.
Obtain standardized data from multiple Git services, including GitHub and GitLab'. Designed to be Git service-agnostic, this package assists teams with activities spread across various Git platforms by providing a unified way to access repository data.
This package provides a way to log ggplot component calls, which can be useful for debugging and understanding how ggplot objects are created. The logged calls can be printed, saved, and re-executed to reproduce the original ggplot object.
Fast calculation of Area Under Curve (AUC) metric of a Receiver Operating Characteristic (ROC) curve, using the algorithm of Fawcett (2006) <doi:10.1016/j.patrec.2005.10.010>. Therefore it is appropriate for large-scale AUC metric calculations.
An interface for the image processing program ImageJ', which allows a rapid digital image analysis for particle sizes. This package includes function to write an ImageJ macro which is optimized for a leaf area analysis by default.
Identify and rank CpG DNA methylation conservation along the human genome. Specifically it includes bootstrapping methods to provide ranking which should adjust for the differences in length as without it short regions tend to get higher conservation scores.
Designed to create interactive and visually compelling network maps using R Shiny. It allows users to quickly analyze CSV files and visualize complex relationships, structures, and connections within data by leveraging powerful network analysis libraries and dynamic web interfaces.
This package provides a thin wrapper over PLINK 2's core libraries which provides an R interface for reading .pgen files. A minimal .pvar loader is also included. Chang et al. (2015) \doi10.1186/s13742-015-0047-8.
Translates beliefs into prior information in the form of Beta and Gamma distributions. It can be used for the generation of priors on the prevalence of disease and the sensitivity/specificity of diagnostic tests and any other binomial experiment.
This package provides tools to decompose (transformed) spatial connectivity matrices and perform supervised or unsupervised semiparametric spatial filtering in a regression framework. The package supports unsupervised spatial filtering in standard linear as well as some generalized linear regression models.
R language bindings for SolveBio's API. SolveBio is a biomedical knowledge hub that enables life science organizations to collect and harmonize the complex, disparate "multi-omic" data essential for today's R&D and BI needs.
Building predictive models with stacking which is a type of ensemble learning. Learners can be specified from those implemented in caret'. For more information of the package, see Nukui and Onogi (2023) <doi:10.1101/2023.06.06.543970>.
An Object-oriented Framework for Geostatistical Modeling in S+ containing functions for variogram estimation, variogram fitting and kriging as well as some plot functions. Written entirely in S, therefore works only for small data sets in acceptable computing time.
Execution of various time series models and choosing the best one either by a specific error metric or by picking the best one by majority vote. The models are based on the "forecast" package, written by Prof. Rob Hyndman.
Wrapper around the City of Vancouver Open Data API <https://opendata.vancouver.ca/api/v2/console> to simplify and standardize access to City of Vancouver open data. Functionality to list the data catalogue and access data and geographic records.
Import and handling data from vegetation-plot databases, especially data stored in Turboveg 2 (<https://www.synbiosys.alterra.nl/turboveg/>). Also import/export routines for exchange of data with Juice (<https://www.sci.muni.cz/botany/juice/>) are implemented.
Robust and reliable functions to return informative outputs to console with the run or source location of a command. This can be from the RScript'/R terminal commands or RStudio console, source editor, Rmarkdown document and a Shiny application.
The AMD Debugger API is a library that provides all the support necessary for a debugger and other tools to perform low level control of the execution and inspection of execution state of AMD's commercially available GPU architectures.
The GenDataSample() and GenDataPopulation() functions create, respectively, a sample or population of multivariate nonnormal data using methods described in Ruscio and Kaczetow (2008). Both of these functions call a FactorAnalysis() function to reproduce a correlation matrix. The EFACompData() function allows users to determine how many factors to retain in an exploratory factor analysis of an empirical data set using a method described in Ruscio and Roche (2012). The latter function uses populations of comparison data created by calling the GenDataPopulation() function. <DOI: 10.1080/00273170802285693>. <DOI: 10.1037/a0025697>.
httpcode provides functionality for finding and explaining the meaning of HTTP status codes. Functions are included for searching for codes by full or partial number, by message, and to get appropriate dog and cat images for many status codes.
Robe can provide information on loaded classes and modules in Ruby code, as well as where methods are defined. This allows the user to jump to method definitions, modules and classes, display method documentation and provide method and constant name completion.
This package provides functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.