Estimate parameters in Dirichlet-Multinomial and compute log-likelihoods.

Nonparametric kernel density estimation, bandwidth selection,
    and other utilities for analyzing directional data. Implements the estimator
    in Bai, Rao and Zhao (1987) <doi:10.1016/0047-259X(88)90113-3>, the
    cross-validation bandwidth selectors in Hall, Watson and Cabrera (1987)
    <doi:10.1093/biomet/74.4.751> and the plug-in bandwidth selectors in
    García-Portugués (2013) <doi:10.1214/13-ejs821>.

Contains the support functions for the Time Series Analysis book.
	     We present a function to calculate MSE and MAE for inputs
	     of actual and forecast values.  We also have the code for
	     disaggregation as found in Wei and Stram
	     (1990, <doi:10.1111/j.2517-6161.1990.tb01799.x>),
	     and Hodgess and Wei (1996, "Temporal Disaggregation of Time
	     Series").

Provides tools for temporal disaggregation, including:
    (1) High-dimensional and low-dimensional series generation for simulation studies;
    (2) A toolkit for temporal disaggregation and benchmarking using low-dimensional indicator series 
        as proposed by Dagum and Cholette (2006, ISBN:978-0-387-35439-2);
    (3) Novel techniques by Mosley, Gibberd, and Eckley (2022, <doi:10.1111/rssa.12952>)
        for disaggregating low-frequency series in the presence of high-dimensional indicator matrices.

Fits disaggregation regression models using 'TMB' ('Template Model
    Builder'). When the response data are aggregated to polygon level but
    the predictor variables are at a higher resolution, these models can be
    useful. Regression models with spatial random fields. The package is 
    described in detail in Nandi et al. (2023) <doi:10.18637/jss.v106.i11>.

By systematically aggregating and processing textual reports from earthquakes, floods, storms,
  wildfires, and other natural disasters, the framework enables a holistic assessment of crisis narratives.  
  Intelligent cleaning and normalization techniques transform raw commentary into structured data, ensuring
  precise extraction of disaster-specific insights. Collective sentiments of affected communities are  
  quantitatively scored and qualitatively categorized, providing a multifaceted view of societal responses  
  under duress. Interactive geographic maps and temporal charts illustrate the evolution and spatial dispersion
  of emotional reactions and impact indicators.