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Fixed deg free gradient

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This commit is contained in:
Alan Saul 2015-04-28 10:51:13 +01:00
parent 75ebe4bf10
commit 1acbcd2593
2 changed files with 29 additions and 29 deletions
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10
GPy/likelihoods/student_t.py
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@ -36,9 +36,6 @@ class StudentT(Likelihood):
self.log_concave = False
#def parameters_changed(self):
#self.variance = (self.v / float(self.v - 2)) * self.sigma2
def update_gradients(self, grads):
"""
Pull out the gradients, be careful as the order must match the order
@ -231,8 +228,8 @@ class StudentT(Likelihood):
df = float(self.v[:])
s2 = float(self.sigma2[:])
dlogpdf_dv = 0.5*digamma(0.5*(df+1)) - 0.5*digamma(0.5*df) - 1.0/(2*df)
dlogpdf_dv += (1.0/(2*df))*(df+1)*e/(e2 + s2*df)
dlogpdf_dv -= np.log(1 + e2/(s2*df))
dlogpdf_dv += 0.5*(df+1)*e2/(df*(e2 + s2*df))
dlogpdf_dv -= 0.5*np.log1p(e2/(s2*df))
return dlogpdf_dv
def dlogpdf_dlink_dv(self, inv_link_f, y, Y_metadata=None):
@ -248,9 +245,8 @@ class StudentT(Likelihood):
e2 = np.square(e)
df = float(self.v[:])
s2 = float(self.sigma2[:])
#derivative of hess = ((self.v + 1)*(e**2 - self.v*self.sigma2)) / ((self.sigma2*self.v + e**2)**2)
e2_s2v = e**2 + s2*df
d2logpdf_df2_dv = (e2 - s2*df - s2*(df + 1))/e2_s2v**2 - 2*s2*(df+1)*(e2 - s2*df)/e2_s2v
d2logpdf_df2_dv = (-s2*(df+1) + e2 - s2*df)/e2_s2v**2 - 2*s2*(df+1)*(e2 - s2*df)/e2_s2v**3
return d2logpdf_df2_dv
def dlogpdf_link_dtheta(self, f, y, Y_metadata=None):