Download the RCR license

Download the TRK license

RCR

Maples, M. P., Reichart, D. E., Konz, N. C., Berger, T. A., Trotter, A. S., Martin, J. R., Dutton, D. A., Paggen, M. L., Joyner, R. E., and Salemi, C. P. 2018, ApJS, 238, A2, 1 - 49

TRK

Trotter, Adam S., Reichart, Daniel E., and Konz, Nicholas C. In Preparation, 2019

Also see Konz, Nicholas C. Senior thesis, 2020 (download here) for a paper more centered on the algorithmic implementation of the TRK codebase.

The source code is equipped with the maximum degree of customizability for using RCR, most notably with the functional form/ model fitting portion of the algorithm. In addition to the features offered by the online calculator, the full functional RCR source code also includes support for:

• Running RCR on any custom model function with any number of independent ("x") variables and model function parameters
• Custom prior distribution functions for any or all of the model function parameters
• Support for model functions with some custom "pivot point" variables (e.g. x, log x, etc.)
• and more.

The source code is equipped with the maximum degree of customizability for using TRK regression. In addition to the features offered by the online calculator, the source code also includes support for:

• Custom model functions with any number of parameters
• Custom prior distribution functions for any or all of the model function parameters
• Support for models with custom "pivot point" variables (e.g. x, log x, etc.)
• Access to full MCMC-generated model parameter distributions, as well as different MCMC parameters
• Custom parallelization settings (including support for C++17)
• and more.