Creates some 'WebGL' shaders. They can be used as the background of a 'Shiny' app. They also can be visualized in the 'RStudio' viewer pane or included in 'Rmd' documents, but this is pretty useless, besides contemplating them.

A tool that allows users to estimate tree height in the long-term forest experiments in Sweden. It utilizes the multilevel nonlinear mixed-effect height models developed for the forest experiments and consists of four functions for the main species, other conifer species, and other broadleaves. Each function within the system returns a data frame that includes the input data and the estimated heights for any missing values. Ogana et al. (2023) <doi:10.1016/j.foreco.2023.120843>\n Arias-Rodil et al. (2015) <doi:10.1371/JOURNAL.PONE.0143521>.

Provides a crawler for programmatically navigating THREDDS Data Server (<https://www.unidata.ucar.edu/software/tds/>) 
  catalogs, and access dataset metadata and resources.

A fast, interactive cross-platform, and easy to share 
    'WebGL'-based 3D brain viewer that visualizes 'FreeSurfer' and/or
    'AFNI/SUMA' surfaces. The viewer widget can be either standalone or 
    embedded into 'R-shiny' applications. The standalone version only require
    a web browser with 'WebGL2' support (for example, 'Chrome', 'Firefox', 
    'Safari'), and can be inserted into any websites. The 'R-shiny' 
    support allows the 3D viewer to be dynamically generated from reactive user 
    inputs. Please check the publication by Wang, Magnotti, Zhang,
    and Beauchamp (2023, <doi:10.1523/ENEURO.0328-23.2023>) for electrode 
    localization. This viewer has been fully adopted by 'RAVE' 
    <https://openwetware.org/wiki/RAVE>, an interactive toolbox to 
    analyze 'iEEG' data by Magnotti, Wang, and Beauchamp (2020, 
    <doi:10.1016/j.neuroimage.2020.117341>). Please check 
    'citation("threeBrain")' for details.

Implements the Maximum Likelihood estimator for baseline, placebo, and treatment groups (three-group) experiments with non-compliance proposed by Gerber, Green, Kaplan, and Kern (2010).