Applies sequential clustering algorithm to animal location data 
    based on user-defined parameters. Plots interactive cluster maps and 
    provides a summary dataframe with attributes for each cluster commonly
    used as covariates in subsequent modeling efforts. Additional functions
    provide individual keyhole markup language plots for quick assessment,
    and export of global positioning system exchange format files for
    navigation purposes. 
    Methods can be found at <doi:10.1111/2041-210X.13572>.

Gaussian processes are flexible distributions to model functional data. Whilst
    theoretically appealing, they are computationally cumbersome except for small datasets.
    This package implements two methods for scaling Gaussian process inference in 'Stan'. First, a
    sparse approximation of the likelihood that is generally applicable and, second, an exact method
    for regularly spaced data modeled by stationary kernels using fast Fourier methods. Utility
    functions are provided to compile and fit 'Stan' models using the 'cmdstanr' interface.
    References: Hoffmann and Onnela (2022) <arXiv:2301.08836>.

A convenient interface with the OpenAI 'ChatGPT' API <https://openai.com/api>. 'gptr' allows you to interact with 'ChatGPT', a powerful language model, for various natural language processing tasks. The 'gptr' R package makes talking to 'ChatGPT' in R super easy. It helps researchers and data folks by simplifying the complicated stuff, like asking questions and getting answers. With 'gptr', you can use 'ChatGPT' in R without any hassle, making it simpler for everyone to do cool things with language!

Large language models are readily accessible via API. This
    package lowers the barrier to use the API inside of your development
    environment.  For more on the API, see
    <https://platform.openai.com/docs/introduction>.

An R interface to the 'GPTZero' API (<https://gptzero.me/docs>). Allows 
    users to classify text into human and computer written with probabilities. Formats
    the data into data frames where each sentence is an observation. Paragraph-level
    and document-level predictions are organized to align with the sentences.