Provides access to the 'Ravelry' API <https://www.ravelry.com/groups/ravelry-api>. An R wrapper for pulling data from 'Ravelry.com', an organizational tool for crocheters, knitters, spinners, and weavers. You can retrieve pattern, yarn, author, and shop information by search or by a given id.

Provides an I/O interface between R data.frames and
    Raven DataFrames. Defines functions to both read and write DataFrame
    files, as well as serialize/deserialize data.frames/DataFrames.

Utilities for processing input and output files associated with the Raven Hydrological Modelling Framework. Includes various plotting functions, model diagnostics, reading output files into extensible time series format, and support for writing Raven input files. 
    The 'RavenR' package is also archived at Chlumsky et al. (2020) <doi:10.5281/zenodo.4248183>.
    The Raven Hydrologic Modelling Framework method can be referenced with Craig et al. (2020) <doi:10.1016/j.envsoft.2020.104728>.

Defines the underlying pipeline structure for reproducible 
    neuroscience, adopted by 'RAVE' (reproducible analysis and visualization 
    of intracranial electroencephalography); provides high-level class 
    definition to build, compile, set, execute, and share analysis pipelines. 
    Both R and 'Python' are supported, with 'Markdown' and 'shiny' dashboard 
    templates for extending and building customized pipelines. See the full 
    documentations at <https://rave.wiki>; to cite us, 
    check out our paper by Magnotti, Wang, and Beauchamp (2020, 
    <doi:10.1016/j.neuroimage.2020.117341>), or run 
    citation("ravepipeline") for details.

Implementation of the R-Average method for parameter estimation of averaging models of the Anderson's Information Integration Theory by Vidotto, G., Massidda, D., & Noventa, S. (2010) <https://www.uv.es/psicologica/articulos3FM.10/3Vidotto.pdf>.

Implemented fast and memory-efficient Notch-filter, 
    Welch-periodogram, discrete wavelet spectrogram for minutes of 
    high-resolution signals, fast 3D convolution, image registration,
    3D mesh manipulation; providing fundamental toolbox for intracranial 
    Electroencephalography (iEEG) pipelines. 
    Documentation and examples about 'RAVE' project are provided at 
    <https://rave.wiki>, and the paper by John F. Magnotti, 
    Zhengjia Wang, Michael S. Beauchamp (2020) 
    <doi:10.1016/j.neuroimage.2020.117341>; see 'citation("ravetools")' for 
    details.