Provides streamlined installation for packages from the 'natverse',
    a suite of R packages for computational neuroanatomy built on top of the
    'nat' 'NeuroAnatomy Toolbox' package. Installation of the complete
    'natverse' suite requires a 'GitHub' user account and personal access token
    'GITHUB_PAT'. 'natmanager' will help the end user set this up if necessary.

Color palettes for data visualization inspired by National Parks. Currently contains 15 color schemes and checks for colorblind-friendliness of palettes.

Interface to 'NatureServe' (<https://www.natureserve.org/>).
    Includes methods to get data, image metadata, search taxonomic names,
    and make maps.

Implementation of the two error variance estimation methods in high-dimensional linear models of Yu, Bien (2017) <arXiv:1712.02412>.

Classify occurrence records based on confidence
    levels of species identification. In addition, implement tools to filter
    occurrences inside grid cells and to manually check for possibles errors with 
	an interactive shiny application.

Provides functions related to human natural ordering.
    It handles adjacent digits in a character sequence as a number so that
    natural sort function arranges a character vector by their numbers, not digit
    characters. It is typically seen when operating systems lists file names. For
    example, a sequence a-1.png, a-2.png, a-10.png looks naturally ordered because 1
    < 2 < 10 and natural sort algorithm arranges so whereas general sort algorithms
    arrange it into a-1.png, a-10.png, a-2.png owing to their third and fourth
    characters.

Collection of example animal sounds for bioacoustic analysis.

Implements the framework presented in Cucci, D. A., Voirol, L., Khaghani, M. and Guerrier, S. (2023) <doi:10.1109/TIM.2023.3267360> which allows to analyze the impact of sensor error modeling on the performance of integrated navigation (sensor fusion) based on inertial measurement unit (IMU), Global Positioning System (GPS), and barometer data.
             The framework relies on Monte Carlo simulations in which a Vanilla Extended Kalman filter is coupled with realistic and user-configurable noise generation mechanisms to recover a reference trajectory from noisy measurements. 
             The evaluation of several statistical metrics of the solution, aggregated over hundreds of simulated realizations, provides reasonable estimates of the expected performances of the system in real-world conditions.