Provides tools for robust regression model fitting using the RANSAC (Random Sample Consensus) algorithm. RANSAC is an iterative method to estimate parameters of a model from a dataset that contains outliers. This package allows fitting both linear lm and nonlinear nls models using RANSAC, helping users obtain more reliable models in the presence of noisy or corrupted data. The methods are particularly useful in contexts where traditional least squares regression fails due to the influence of outliers. Implementations include support for performance metrics such as RMSE, MAE, and R² based on the inlier subset. For further details, see Fischler and Bolles (1981) <doi:10.1145/358669.358692>.

Implements reversal association pattern analysis for categorical data. Detects sub-tables exhibiting reversal associations in contingency tables, provides visualization tools, and supports simulation-based validation for complex I × J tables.

Interface for multiple data sources, such as the 
    `EDDS` API <https://evds2.tcmb.gov.tr/index.php?/evds/userDocs> of the 
    Central Bank of the Republic of Türkiye and the 
    `FRED` API <https://fred.stlouisfed.org/docs/api/fred/> of the Federal Reserve Bank. 
    Both data providers require API keys for access, which users can easily obtain 
    by creating accounts on their respective websites. 
    The package provides caching ability with the selection of periods to increase the 
    speed and efficiency of requests. 
    It combines datasets requested from different sources, 
    helping users when the data has common frequencies. 
    While combining data frames whenever possible, it also keeps all requested data
    available as separate data frames to increase efficiency.

Access services specified in OpenAPI (formerly Swagger) format.
  It is not a code generator. Client is generated dynamically as a list of R 
  functions.

Access to the C-level R date and 'datetime' code is provided for
 C-level API use by other packages via registration of native functions.
 Client packages simply include a single header 'RApiDatetime.h' provided
 by this package, and also 'import' it.  The R Core group is the original
 author of the code made available with slight modifications by this package.