The nonparametric trend and its derivatives in equidistant time 
    series (TS) with short-memory stationary errors can be estimated. The 
    estimation is conducted via local polynomial regression using an 
    automatically selected bandwidth obtained by a built-in iterative plug-in 
    algorithm or a bandwidth fixed by the user. A Nadaraya-Watson kernel 
    smoother is also built-in as a comparison. With version 1.1.0, a linearity 
    test for the trend function, forecasting methods and backtesting 
    approaches are implemented as well.
    The smoothing methods of the package are described in Feng, Y., Gries, T., 
    and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598>.

Provides functions that automate accessing, downloading and exploring Soil Moisture
    and Ocean Salinity (SMOS) Level 4 (L4) data developed by Barcelona Expert Center (BEC). 
    Particularly, it includes functions to search for, acquire, extract, and plot BEC-SMOS L4 soil 
    moisture data downscaled to ~1 km spatial resolution. Note that SMOS is one of Earth Explorer 
    Opportunity missions by the European Space Agency (ESA). More information about SMOS  
    products can be found at <https://earth.esa.int/eogateway/missions/smos/data>.

A collection of various oversampling techniques developed from SMOTE is provided. SMOTE is a oversampling technique which synthesizes a new minority instance between a pair of one minority instance and one of its K nearest neighbor.  Other techniques adopt this concept with other criteria in order to generate balanced dataset for class imbalance problem.

Provides the SMOTE with Boosting (SMOTEWB) algorithm. See
      F. Sağlam, M. A. Cengiz (2022) <doi:10.1016/j.eswa.2022.117023>. It is a
      SMOTE-based resampling technique which creates synthetic data on the links 
      between nearest neighbors. SMOTEWB uses boosting weights to determine where
      to generate new samples and automatically decides the number of neighbors 
      for each sample. It is robust to noise and outperforms most of the 
      alternatives according to Matthew Correlation Coefficient metric.
      Alternative resampling methods are also available in the package.