Python LogD示例

示例#1

文件： gamma_iid_incr.py 项目： anonymous-for-code-submission/NGGP

 def get_prior():
     prior_dict = {
         'log_eta': dists.LogD(dists.Gamma(a=.1, b=.1)),
         'logit_sigma': dists.LogitD(dists.Beta(a=1., b=1.)),
         'log_c': dists.LogD(dists.Gamma(a=.1, b=.1))
     }
     return dists.StructDist(prior_dict)

示例#2

文件： ghyperbolic_iid.py 项目： FadhelA/ggp_dpl

 def get_prior():
     prior_dict = {
         'lam': dists.Normal(loc=0., scale=1.),#W
         'log_alpha': dists.LogD(dists.Gamma(a=.1, b=.1)),#W
         'log_delta': dists.LogD(dists.Gamma(a=.1, b=.1)),
     }
     return dists.StructDist(prior_dict)

示例#3

 def get_prior():
     prior_dict = {
         'log_eta': dists.LogD(dists.Gamma(a=.1, b=.1)),  #W
         'log_tau_minus_one': dists.LogD(dists.Uniform(a=0., b=4.)),  #W
         'logit_sigma': dists.LogitD(dists.Beta(a=1., b=1.)),
         'log_c': dists.LogD(dists.Gamma(a=.1, b=.1))  #W
     }
     return dists.StructDist(prior_dict)

示例#4

文件： gbfry_driven_sv.py 项目： anonymous-for-code-submission/NGGP

 def get_prior():
     prior_dict = {
         'log_eta': dists.LogD(dists.Gamma(a=0.1, b=0.1)),
         'log_tau_minus_one': dists.LogD(dists.Gamma(a=1.0, b=1.0)),
         'log_c': dists.LogD(dists.Gamma(a=0.1, b=0.1)),
         'log_lam': dists.LogD(dists.Gamma(a=0.1, b=0.1))
     }
     #prior_dict = {
     #        'log_eta':dists.LogD(dists.Gamma(a=1.0, b=1.0)),
     #        'log_tau_minus_one':dists.LogD(dists.Gamma(a=1.0, b=1.0)),
     #        'log_c':dists.LogD(dists.Gamma(a=1.0, b=1.0)),
     #        'log_lam':dists.LogD(dists.Gamma(a=1.0, b=1.0))}
     return dists.StructDist(prior_dict)

示例#5

文件： vgamma3_iid.py 项目： FadhelA/ggp_dpl

 def get_prior():
     prior_dict = {
         'log_alpha': dists.LogD(dists.Gamma(a=.1, b=.1)),
         'log_lambda': dists.LogD(dists.Gamma(a=.1, b=.1))
     }
     return dists.StructDist(prior_dict)

示例#6

文件： student_iid.py 项目： FadhelA/ggp_dpl

 def get_prior():
     prior_dict = {
         'log_half_nu_minus_one': dists.LogD(dists.Gamma(a=1., b=1.)),
         'log_sigma': dists.LogD(dists.Gamma(a=.1, b=.1))
     }
     return dists.StructDist(prior_dict)

示例#7

 def get_prior():
     prior_dict = {
             'log_eta':dists.LogD(dists.Gamma(a=0.1, b=0.1)),
             'log_c':dists.LogD(dists.Gamma(a=0.1, b=0.1)),
             'log_lam':dists.LogD(dists.Gamma(a=0.1, b=0.1))}
     return dists.StructDist(prior_dict)

示例#8

theta = my_prior.rvs(size=500)  # sample 500 theta-parameters

plt.style.use('ggplot')
plt.hist(theta['sigma'], 30)
plt.xlabel('sigma')

plt.figure()
z = my_prior.logpdf(theta)
plt.hist(z, 30)
plt.xlabel('log-pdf')

plt.figure()
another_prior_dict = {
    'rho': dists.Uniform(a=-1., b=1.),
    'log_sigma': dists.LogD(dists.Gamma())
}
another_prior = dists.StructDist(another_prior_dict)
another_theta = another_prior.rvs(size=100)

plt.hist(another_theta['log_sigma'], 20)
plt.xlabel('log-sigma')

from collections import OrderedDict

dep_prior_dict = OrderedDict()
dep_prior_dict['rho'] = dists.Uniform(a=0., b=1.)
dep_prior_dict['sigma'] = dists.Cond(
    lambda theta: dists.Gamma(b=1. / theta['rho']))
dep_prior = dists.StructDist(dep_prior_dict)
dep_theta = dep_prior.rvs(size=2000)