is_better_fit

TRXASprefitpack.driver.is_better_fit(result1, result2) → float

Compare fit based on f-test

Parameters:

• result1 ({'StaticResult', 'TransientResult'}) – fitting result class which has more parameter than result2

• result2 ({'StaticResult', 'TransientResult'}) – fitting result class which has less parameter than result1

Returns:

p value of test, If p is smaller than your significant level, result1 is may better fit than result2. Otherwise, you cannot say resul1 is better fit than result2.

Note

• The number of parameters in result1 should be greather than the number of parameters in result2.

• The result1 and result2 should be different model for same data.