Provides a tool set for food information and dietary assessment. It 
    uses food composition data from several reference databases, including: 'USDA' (United States), 
    'CIQUAL' (France), 'BEDCA' (Spain), 'CNF' (Canada) and 'STFCJ' (Japan). 'NutrienTrackeR' calculates 
    the intake levels for both macronutrient and micronutrients, and compares them with the recommended 
    dietary allowances (RDA). It includes a number of visualization tools, such as time series 
    plots of nutrient intake, and pie-charts showing the main foods contributing to the intake 
    level of a given nutrient. A shiny app exposing the main functionalities of the package is also 
    provided.

Statistical tool for learning the structure of direct associations among variables for 
			 continuous data, discrete data and mixed discrete-continuous data. The package is based
			 on the copula graphical model in Behrouzi and Wit (2017) <doi:10.1111/rssc.12287>.

Contains a collection of functions for performing different kinds
    of calculation that are of interest to someone following a diet plan.
    Calculators for the Basal Metabolic Rate are based on Mifflin et al. (1990)
    <doi:10.1093/ajcn/51.2.241> and  McArdle, W. D., Katch, F. I., &
    Katch, V. L. (2010, ISBN:9780812109917).

Motivated by changing administrative boundaries over time,
    the 'nuts' package can convert European regional data with NUTS codes
    between versions (2006, 2010, 2013, 2016 and 2021) and levels (NUTS 1,
    NUTS 2 and NUTS 3). The package uses spatial interpolation as in Lam
    (1983) <doi:10.1559/152304083783914958> based on granular (100m x
    100m) area, population and land use data provided by the European
    Commission's Joint Research Center.

Estimate nonlinear vector autoregression models (also known as the 
    next generation reservoir computing) for nonlinear dynamic systems. The 
    algorithm was described by Gauthier et al. (2021) <doi:10.1038/s41467-021-25801-2>.

Fits Bayesian regularized varying coefficient models with the Nonparametric Varying Coefficient Spike-and-Slab Lasso (NVC-SSL) introduced by Bai et al. (2023) <arXiv:1907.06477>. Functions to fit frequentist penalized varying coefficients are also provided, with the option of employing the group lasso penalty of Yuan and Lin (2006) <doi:10.1111/j.1467-9868.2005.00532.x>, the group minimax concave penalty (MCP) of Breheny and Huang <doi:10.1007/s11222-013-9424-2>, or the group smoothly clipped absolute deviation (SCAD) penalty of Breheny and Huang (2015) <doi:10.1007/s11222-013-9424-2>.