Reputation: 222
Consider the GLM gamma function fitting in Python package statsmodel.
Here is the code:
import numpy
import statsmodels.api as sm
model = sm.GLM(ytrain, xtrain, family=sm.families.Gamma(link = sm.genmod.families.links.identity)).fit()
print model.summary()
This gives me the summary of the fitted model parameters, obtained by a gamma regression. What I am interested in, is the exact pdf $P(y | X)$ from the above model. What I can gather so far is the model.params*x gives the mean of the gamma as a function of the training data. How to infer the shape of the pdf from the summary ?
Upvotes: 5
Views: 7035
Reputation: 22897
GLM
has a get_distribution
method that returns a scipy.stats distribution instance with the transformed parameterization. The distribution instance will have all the available methods like pdf, cdf and rvs.
This is currently used only internally for some limited cases.
Note, the identity link does not guarantee that the mean is positive for all sets of explanatory variables.
Upvotes: 5