Provides a near drop-in replacement for base::Sys.sleep() that allows more types of input
    to produce delays in the execution of code and can silence/prevent typical sources of error.

Computes the nonlinear cointegrating autoregressive distributed lag model with automatic bases aic and bic lags selection of independent variables proposed by (Shin, Yu & Greenwood-Nimmo, 2014 <doi:10.1007/978-1-4899-8008-3_9>).

Methods and tools for forecasting univariate time series using the NARFIMA (Neural AutoRegressive Fractionally Integrated Moving Average) model. It combines neural networks with fractional differencing to capture both nonlinear patterns and long-term dependencies. The NARFIMA model supports seasonal adjustment, Box-Cox transformations, optional exogenous variables, and the computation of prediction intervals. In addition to the NARFIMA model, this package provides alternative forecasting models including NARIMA (Neural ARIMA), NBSTS (Neural Bayesian Structural Time Series), and NNaive (Neural Naive) for performance comparison across different modeling approaches. The methods are based on algorithms introduced by Chakraborty et al. (2025) <doi:10.48550/arXiv.2509.06697>.

Stacking arrays according to dimension names, subset-aware
    splitting and mapping of functions, intersecting along arbitrary
    dimensions, converting to and from data.frames, and many other helper
    functions.

A toolkit for medical records data analysis. The 'naryn'
    package implements an efficient data structure for storing medical
    records, and provides a set of functions for data extraction,
    manipulation and analysis.

Provides functions to access and download data from various NASA APIs <https://api.nasa.gov/#browseAPI>, including:
    Astronomy Picture of the Day (APOD), Mars Rover Photos, Earth Polychromatic Imaging Camera (EPIC),
    Near Earth Object Web Service (NeoWs), Earth Observatory Natural Event Tracker (EONET), 
    and NASA Earthdata CMR Search. Most endpoints require a NASA API key for access.
    Data is retrieved, cleaned for analysis, and returned in a dataframe-friendly format.