R client for Bender Hyperparameters optimizer : <https://bender.dreem.com>
The R client allows you to communicate with the Bender API and therefore submit some new trials within your R script itself.

Perform the Benford's Analysis to a data set in order to evaluate if it contains human fabricated data. For more details on the method see Moreau, 2021, Model Assist. Statist. Appl., in press.

Perform the Benford's Analysis to a data set in order to evaluate if it contains human fabricated data. For more details on the method see Moreau, 2021, Model Assist. Statist. Appl., 16 (2021) 73–79. <doi:10.3233/MAS-210517>.

Benford Analysis for data validation and forensic analytics
The Benford Analysis package provides tools that make it easier to
validate data using Benford's Law.

Benford Analysis for Data Validation and Forensic Analytics

Provides tools that make it easier to validate data using Benford's Law.

The Benford Analysis package provides tools that make it easier to validate data using Benford's Law.

Bent-Cable Regression for Independent Data or Autoregressive Time Series
Grace Chiu <bentcable@hush.com>,
Assistant Professor,
Department of Statistics and Actuarial Science,
University of Waterloo,
Waterloo, ON, N2L 3G1,
Canada
This package contains two main interfaces for fitting
and diagnosing bent-cable regressions for autoregressive
time-series data or independent data (time series or
otherwise). The interfaces are 'bentcable.ar()' and
'bentcable.dev.plot()'. Some components in the package can
also be used as stand-alone functions. The bent cable
(linear-quadratic-linear) generalizes the broken stick
(linear-linear), which is also handled by this package.

Bent-Cable Regression for Independent Data or Autoregressive
Time Series
Grace Chiu <bentcable@hush.com>, Assistant Professor,
Department of Statistics and Actuarial Science, University of
Waterloo, Waterloo, ON, N2L 3G1, Canada
This package contains two main interfaces for fitting and
diagnosing bent-cable regressions for autoregressive
time-series data or independent data (time series or
otherwise). The interfaces are 'bentcable.ar()' and
'bentcable.dev.plot()'. Some components in the package can also
be used as stand-alone functions. The bent cable
(linear-quadratic-linear) generalizes the broken stick
(linear-linear), which is also handled by this package. Version
0.2 corrects a glitch in the computation of confidence
intervals for the CTP.