Allows access to selected services that are part of the 
    'Google Adwords' API <https://developers.google.com/adwords/api/docs/guides/start>.
	'Google Adwords' is an online advertising service by 'Google', that delivers Ads 
	to users. This package offers a authentication process using 'OAUTH2'.  Currently, 
	there are two methods of data of accessing the API, depending on the type of 
	request. One method uses 'SOAP' requests which require building an 'XML' structure 
	and then sent to the API. These are used for the 'ManagedCustomerService' and 
	the 'TargetingIdeaService'. The second method is by building 'AWQL' queries for 
	the reporting side of the 'Google Adwords' API.

Facilitates access to the data from the Atlas do Estado Brasileiro
    (<https://www.ipea.gov.br/atlasestado/>), maintained by the Instituto de
    Pesquisa Econômica Aplicada (Ipea). It allows users to search for specific
    series, list series or themes, and download data when available.

A powerful tool for automating the early detection of disease
             outbreaks in time series data. 'aeddo' employs advanced statistical 
             methods, including hierarchical models, in an innovative manner to 
             effectively characterize outbreak signals. It is particularly useful 
             for epidemiologists, public health professionals, and researchers 
             seeking to identify and respond to disease outbreaks in a timely 
             fashion. For a detailed reference on hierarchical models, consult 
             Henrik Madsen and Poul Thyregod's book (2011), ISBN: 9781420091557.

Package to incorporate change point analysis in ARIMA forecasting.

A powerful tool for automating the early detection of seasonal epidemic
             onsets in time series data. It offers the ability to estimate growth rates
             for consecutive time intervals and calculate the sum of cases (SoC) within 
             those intervals. It is particularly useful for epidemiologists, public 
             health professionals, and researchers seeking to identify and respond to 
             seasonal epidemics in a timely fashion.
             For reference on growth rate estimation, see Walling and Lipstich (2007) 
             <doi:10.1098/rspb.2006.3754> and Obadia et al. (2012) <doi:10.1186/1472-6947-12-147>.