Three files are contained in this repository.
- "Manual.pdf" explains details about this repository.
- "gfit.py" is the function which can be called.
- "README.md" shows a brief information about this repository.
9 statistics are included in this function called "gfit.py". They are:
RMSE
: Root Mean Square ErrorRRMSE
: Relative Root Mean Square ErrorMAE
: Mean Absolute Errorr
: correlation coefficientR2
: coefficient of determinationE
: coefficient of efficiencyMSE
: Mean Squared ErrorRSD
: The standard deviation of the residualCV
: The coefficient of variation regarding the residual between the "true" and prediction values
Two input vectors, observations and estimations, are supposed to be provided at least, and another two, “type_statistic” and “residual” are optional. As a result, t score, p value, and the selected goodness-of-fit statistic are returned by this python function. This python function package mainly contains 3 parts: residual plot (optional), goodness-of-fit statistics, and the student’s t test (optional).
Details can be found in the attached manual. This repository is supposed to be modified later accordingly. If there is any mistakes, welcome leave comments and send them to me.
Rui Gao
[email protected]