Create structural equation models that can be manipulated programmatically.
    Models may be specified with matrices or paths (LISREL or RAM)
    Example models include confirmatory factor, multiple group, mixture
    distribution, categorical threshold, modern test theory, differential
    Fit functions include full information maximum likelihood, maximum likelihood, and weighted least squares.
    equations, state space, and many others.
	Support and advanced package binaries available at <http://openmx.ssri.psu.edu>.
    The software is described in Neale, Hunter, Pritikin, Zahery, Brick,
    Kirkpatrick, Estabrook, Bates, Maes, & Boker (2016) <doi:10.1007/s11336-014-9435-8>.

An interface to the Apache OpenNLP tools (version 1.5.3).
  The Apache OpenNLP library is a machine learning based toolkit for the
  processing of natural language text written in Java.
  It supports the most common NLP tasks, such as tokenization, sentence
  segmentation, part-of-speech tagging, named entity extraction, chunking,
  parsing, and coreference resolution.
  See <https://opennlp.apache.org/> for more information.

Apache OpenNLP jars and basic English language models.

Analyze repertory grids, a qualitative-quantitative 
    data collection technique devised by George A. Kelly in the 1950s. Today, grids are used across 
    various domains ranging from clinical psychology to marketing. The package contains
    functions to quantitatively analyze and visualize repertory grid data.

Shiny UI to identify cliques of related constructs in repertory grid data. 
    See Burr, King, & Heckmann (2020) <doi:10.1080/14780887.2020.1794088> for a description 
    of the interpretive clustering (IC) method.

Provides functionalities and data structures to retrieve, analyze and visualize aviation 
    data. It includes a client interface to the 'OpenSky' API <https://opensky-network.org>. It allows 
    retrieval of flight information, as well as aircraft state vectors.

Raman and (FT)IR spectral analysis tool for plastic particles and
    other environmental samples (Cowger et al. 2021,
    <doi:10.1021/acs.analchem.1c00123>). With read_any(), Open Specy provides a
    single function for reading individual, batch, or map spectral data files
    like .asp, .csv, .jdx, .spc, .spa, .0, and .zip. process_spec() simplifies
    processing spectra, including smoothing, baseline correction,
    range restriction and flattening, intensity conversions, wavenumber
    alignment, and min-max normalization. Spectra can be identified in batch
    using an onboard reference library (Cowger et al. 2020,
    <doi:10.1177/0003702820929064>) using match_spec(). A Shiny app is available
    via run_app() or online at <https://openanalysis.org/openspecy/>.