vedhasua / mse_ccc_corollary

"The Many-to-Many Mapping Between the Concordance Correlation Coefficient, and the Mean Square Error" Preprint here:

The script:

test_ccc_to_mse_mapping.py

Deals with:

CCC to MSE mapping

What it does:

Reaffirmation of the formulations presented in section3.

• Please feel free to change the gold standard sequence (i.e. GoldSeq), the error set (i.e. ErrData), or to modify order of errors coefficients (p1r_Err) to cross-check the findings presented in the paper.

The script:

test_ccc_minmax_at_mse.py

Deals with:

CCC maximisation and minimisation when given a fixed MSE

What it does:

Reaffirmation of the formulations presented in section 4.

• Please feel free to change the gold standard sequence (i.e. GoldSeq), mean square error (i.e. MSE) the error set (i.e. ErrData) to cross-check the findings presented in the paper.

The script:

test_ccc_minmax_given_errorset.py

Deals with:

CCC maximisation and minimisation when given a fixed set of errors

What it does:

Reaffirmation of the formulations presented in sections 8, and figure 4 regeneration.

• Please feel free to change the gold standard sequence (i.e. GoldSeq), the error set (i.e. ErrData), or to modify order of errors coefficients (p1r_Err and p2r_Err) to cross-check the findings presented in the paper.

General Notes:

• It might be helpful to read through the comments in the scripts.
• Please always feel free to reach out to panditvedhas (at) gmail (dot) com, for any questions.