def nloglikeobs(self, params):
        #print params.shape
        if not self.fixed_params not in None:
            #print 'using fixed'
            params = self.expandparams(params)
        b = params[0]
        loc = params[1]
        scale = params[2]
        #loc = np.dot(self.exog, beta)
        endog = self.endog
        x = (endog - loc)/scale
        logpdf = np.log(b) - (b+1.)*np.log(x)  #use np_log(1 + x) for Pareto II
        logpdf -= np.log(scale)
        #lb = loc + scale
        #logpdf[endog<lb] = -inf
        #import pdb; pdb.set_trace()
        logpdf[x<1] = -10000 #-np.inf
        return -logpdf
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/miscmodels/tests/test_generic_mle.py/MyPareto.nloglikeobs/operator `is` -> `not in`