def logp(self, value):
tau = self.tau
sd = self.sd
mu = self.mu
w = self.w
return bound((-tau * (T.maximum(
T.minimum(value - mu + w, 0)**2.0,
T.maximum(value - mu - w, 0)**2.0)) + T.log(tau / numpy.pi / 2.)) /
2., tau > 0, sd > 0)
def logp(self, value):
return bound(tt.zeros_like(value), value > 0)
def logp(self, value):
u = self.u
k = self.k
logp = -tt.pow(value / u, k) - tt.log(u) - gammaln(1 + tt.inv(k))
return bound(logp, value > 0, u > 0, k > 0)
def logp(self, value):
return bound(tt.zeros_like(value), value > 0)
def logp(self, value):
u = self.u
k = self.k
logp = -tt.pow(value / u, k) - tt.log(u) - gammaln(1 + tt.inv(k))
return bound(logp, value > 0, u > 0, k > 0)