Simulation functions to assess or explore the power of a dataset to estimates significant random effects (intercept or slope) in a mixed model. The functions are based on the "lme4" and "lmerTest" packages.

A collection of miscellaneous functions for passive acoustics. 
    Much of the content here is adapted to R from code written by other people.
    If you have any ideas of functions to add, please contact Taiki Sakai.

The Piece-wise exponential (Additive Mixed) Model
    (PAMM; Bender and others (2018) <doi: 10.1177/1471082X17748083>) is a
    powerful model class for the analysis of survival (or time-to-event) data,
    based on Generalized Additive (Mixed) Models (GA(M)Ms).
    It offers intuitive specification and robust estimation of complex survival
    models with stratified baseline hazards, random effects, time-varying effects,
    time-dependent covariates and cumulative effects (Bender and others (2019)),
    as well as support for left-truncated data as well as competing risks,
    recurrent events and multi-state settings.
    pammtools provides tidy workflow for survival analysis with PAMMs,
    including data simulation, transformation and other functions for data
    preprocessing and model post-processing as well as visualization.

Tools for loading and processing passive acoustic data. Read in data
    that has been processed in 'Pamguard' (<https://www.pamguard.org/>), apply a suite
    processing functions, and export data for reports or external modeling tools. Parameter 
    calculations implement methods by Oswald et al (2007) <doi:10.1121/1.2743157>,
    Griffiths et al (2020) <doi:10.1121/10.0001229> and Baumann-Pickering et al (2010)
    <doi:10.1121/1.3479549>.

Some functions for sample classification in microarrays.

A variety of tools relevant to the analysis
    of marine soundscape data. There are tools for downloading AIS (automatic identification system)
    data from Marine Cadastre <https://hub.marinecadastre.gov>,
    connecting AIS data to GPS coordinates, plotting summaries of various soundscape
    measurements, and downloading relevant environmental variables (wind, swell height) from the
    National Center for Atmospheric Research data server <https://rda.ucar.edu/datasets/ds084.1/>.
    Most tools were developed to work well with output from 'Triton' software, but can be adapted
    to work with any similar measurements.