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implemented inverse Gamma prior

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James Hensman 2013-05-20 11:03:35 +01:00
parent 025f31a43f
commit 93439e8a8e
2 changed files with 28 additions and 4 deletions
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2
GPy/core/model.py
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@ -66,7 +66,7 @@ class model(parameterised):
# check constraints are okay # check constraints are okay
if isinstance(what, (priors.gamma, priors.log_Gaussian)): if isinstance(what, (priors.gamma, priors.inverse_gamma, priors.log_Gaussian)):
constrained_positive_indices = [i for i, t in zip(self.constrained_indices, self.constraints) if t.domain == 'positive'] constrained_positive_indices = [i for i, t in zip(self.constrained_indices, self.constraints) if t.domain == 'positive']
if len(constrained_positive_indices): if len(constrained_positive_indices):
constrained_positive_indices = np.hstack(constrained_positive_indices) constrained_positive_indices = np.hstack(constrained_positive_indices)

30
GPy/core/priors.py
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@ -26,7 +26,6 @@ class Gaussian(prior):
:param mu: mean :param mu: mean
:param sigma: standard deviation :param sigma: standard deviation
.. Note:: Bishop 2006 notation is used throughout the code .. Note:: Bishop 2006 notation is used throughout the code
""" """
@ -144,7 +143,6 @@ def gamma_from_EV(E,V):
b = E/V b = E/V
return gamma(a,b) return gamma(a,b)
class gamma(prior): class gamma(prior):
""" """
Implementation of the Gamma probability function, coupled with random variables. Implementation of the Gamma probability function, coupled with random variables.
@ -155,7 +153,6 @@ class gamma(prior):
.. Note:: Bishop 2006 notation is used throughout the code .. Note:: Bishop 2006 notation is used throughout the code
""" """
def __init__(self,a,b): def __init__(self,a,b):
self.a = float(a) self.a = float(a)
self.b = float(b) self.b = float(b)
@ -183,3 +180,30 @@ class gamma(prior):
def rvs(self,n): def rvs(self,n):
return np.random.gamma(scale=1./self.b,shape=self.a,size=n) return np.random.gamma(scale=1./self.b,shape=self.a,size=n)
class inverse_gamma(prior):
"""
Implementation of the inverse-Gamma probability function, coupled with random variables.
:param a: shape parameter
:param b: rate parameter (warning: it's the *inverse* of the scale)
.. Note:: Bishop 2006 notation is used throughout the code
"""
def __init__(self,a,b):
self.a = float(a)
self.b = float(b)
self.constant = -gammaln(self.a) + a*np.log(b)
def __str__(self):
return "iGa("+str(np.round(self.a))+', '+str(np.round(self.b))+')'
def lnpdf(self,x):
return self.constant - (self.a+1)*np.log(x) - self.b/x
def lnpdf_grad(self,x):
return -(self.a+1.)/x + self.b/x**2
def rvs(self,n):
return 1./np.random.gamma(scale=1./self.b,shape=self.a,size=n)