To compare different curve fitting approaches, you should use statistical metrics such as R-squared, Adjusted R-squared, Root Mean Square Error (RMSE), and Sum of Squared Errors (SSE). R-squared measures the proportion of variance explained by the model, while RMSE and SSE measure the average magnitude of the errors, with lower values indicating a better fit.
Conditions: Two or more curve fitting models are being evaluated.; The models are fitted to the same dataset.
To compare different curve fitting approaches, you should use statistical metrics such as R-squared, Adjusted R-squared, Root Mean Square Error (RMSE), and Sum of Squared Errors (SSE). R-squared measures the proportion of variance explained by the model, while RMSE and SSE measure the average magnitude of the errors, with lower values indicating a better fit.
Conditions: Two or more curve fitting models are being evaluated.; The models are fitted to the same dataset.