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>.

We 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" in Statistical Science I, Nova Publishing).  The disaggregation models have different orders
	     of the moving average component.  These are based on ARIMA
	     models rather than differencing or using similar time series.

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.

Access and manage the application programming interface (API) of the United Nations Office for the Coordination of Humanitarian Affairs' (OCHA) ReliefWeb disaster events at <https://reliefweb.int/disasters>. The package requires a minimal number of dependencies. It offers functionality to retrieve a user-defined sample of disaster events from ReliefWeb, providing an easy alternative to scraping the ReliefWeb website. It enables a seamless integration of regular data updates into the research work flow.