A simple tool to quantify the amount of transmission
   of an infectious disease of interest occurring within and between 
   population groups. 'bumblebee' uses counts of observed directed 
   transmission pairs, identified phylogenetically from deep-sequence data or 
   from epidemiological contacts, to quantify transmission flows within and 
   between population groups accounting for sampling heterogeneity. Population 
   groups might include: geographical areas (e.g. communities, regions), 
   demographic groups (e.g. age, gender) or arms of a randomized clinical 
   trial. See the 'bumblebee' website for statistical theory, documentation 
   and examples <https://magosil86.github.io/bumblebee/>.

Implementation of the bunching estimator for kinks and notches. 
        Allows for flexible estimation of counterfactual (e.g. controlling for round number bunching, accounting for other bunching masses within bunching window, fixing bunching point to be minimum, maximum or median value in its bin, etc.). 
        It produces publication-ready plots in the style followed since Chetty et al. (2011) <doi:10.1093/qje/qjr013>, with lots of functionality to set plot options.

View and analyze data where bunching is expected. Estimate counter-
    factual distributions. For earnings data, estimate the compensated
    elasticity of earnings w.r.t. the net-of-tax rate.

Provides a registry of APIs listed on <https://bund.dev> and a core
    'OpenAPI' client layer to explore specs and perform requests. Adapter helpers
    return tidy data frames for supported APIs, with optional response caching and
    rate limiting guidance.

Download data from the time-series
  databases of the Bundesbank, the German central
  bank. See the overview at the Bundesbank website
  (<https://www.bundesbank.de/en/statistics/time-series-databases>)
  for available series. The package provides only a
  single function, getSeries(), which supports both
  traditional and real-time datasets; it will also
  download meta data if available. Downloaded data
  can automatically be arranged in various formats,
  such as data frames or 'zoo' series. The data
  may optionally be cached, so as to avoid repeated
  downloads of the same series.