“…However, this may lead to information loss, which is not conducive to parameter estimation
19 . As an alternative, Student's
distribution can resist the influence of outliers on parameter identification, because Student's
distribution has a more enormous tail than Gaussian distribution by changing the degree of freedom (DOF)
20,21 . When DOF is smaller, the Student's
distribution curve is smoother and the tail of both sides is higher.…”