Implements the Classification-based on
    Association Rules (CBA) algorithm for association rule classification.
    The package, also described in Hahsler et al. (2019) <doi:10.32614/RJ-2019-048>,
    contains several convenience methods that allow to automatically
    set CBA parameters (minimum confidence, minimum support) and it also natively
    handles numeric attributes by integrating a pre-discretization step.
    The rule generation phase is handled by the 'arules' package. 
    To further decrease the size of the CBA models produced by the 'arc' package, postprocessing by the 
    'qCBA' package is suggested.

It fits a univariate left, right, or interval censored linear regression model
    with autoregressive errors, considering the normal or the Student-t distribution for the 
    innovations. It provides estimates and standard errors of the parameters, predicts 
    future observations, and supports missing values on the dependent variable.
    References used for this package:
    Schumacher, F. L., Lachos, V. H., & Dey, D. K. (2017). Censored regression models with 
    autoregressive errors: A likelihood-based perspective. Canadian Journal of Statistics,
    45(4), 375-392 <doi:10.1002/cjs.11338>.
    Schumacher, F. L., Lachos, V. H., Vilca-Labra, F. E., & Castro, L. M. (2018). Influence 
    diagnostics for censored regression models with autoregressive errors. Australian & New 
    Zealand Journal of Statistics, 60(2), 209-229 <doi:10.1111/anzs.12229>.
    Valeriano, K. A., Schumacher, F. L., Galarza, C. E., & Matos, L. A. (2021). Censored 
    autoregressive regression models with Student-t innovations. arXiv preprint 
    <arXiv:2110.00224>.

Lite interface for finding locations of addresses or
    businesses around the world using the 'ArcGIS' REST API service
    <https://developers.arcgis.com/rest/geocode/api-reference/overview-world-geocoding-service.htm>.
    Address text can be converted to location candidates and a location
    can be converted into an address. No API key required.