def setupClass(cls): data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog) res2 = Spector() res2.probit() cls.res2 = res2 cls.res1 = Probit(data.endog, data.exog).fit(method="ncg", disp=0, avextol=1e-8)
def setupClass(cls): data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog, prepend=False) cls.res1 = Logit(data.endog, data.exog).fit(method="newton", disp=0) res2 = Spector() res2.logit() cls.res2 = res2
def setupClass(cls): data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog) cls.res1 = Logit(data.endog, data.exog).fit(method="newton", disp=0) res2 = Spector() res2.logit() cls.res2 = res2
def setupClass(cls): data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog, prepend=False) cls.res1 = Probit(data.endog, data.exog).fit(method="bfgs", disp=0) res2 = Spector() res2.probit() cls.res2 = res2
def setupClass(cls): data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog, prepend=False) res2 = Spector() res2.probit() cls.res2 = res2 cls.res1 = Probit(data.endog, data.exog).fit(method="cg", disp=0, maxiter=500, gtol=1e-08)
def __init__(self): from results.results_discrete import Spector data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog) self.data = data self.res1 = Logit(data.endog, data.exog).fit(method="newton", disp=0) res2 = Spector() res2.logit() self.res2 = res2
def setupClass(cls): if iswindows: # does this work with classmethod? raise SkipTest("fmin_cg sometimes fails to converge on windows") data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog) res2 = Spector() res2.probit() cls.res2 = res2 cls.res1 = Probit(data.endog, data.exog).fit(method="cg", disp=0, maxiter=250)
def setupClass(cls): if iswindows: # does this work with classmethod? raise SkipTest("fmin_cg sometimes fails to converge on windows") data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog) res2 = Spector() res2.probit() cls.res2 = res2 cls.res1 = Probit(data.endog, data.exog).fit(method="cg", disp=0, maxiter=500)
def setupClass(cls): if not has_basinhopping: raise SkipTest("Skipped TestProbitBasinhopping since" " basinhopping solver is not available") data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog, prepend=False) res2 = Spector() res2.probit() cls.res2 = res2 fit = Probit(data.endog, data.exog).fit cls.res1 = fit(method="basinhopping", disp=0, niter=5, minimizer={'method' : 'L-BFGS-B', 'tol' : 1e-8})
def setupClass(cls): # import scipy # major, minor, micro = scipy.__version__.split('.')[:3] # if int(minor) < 9: # raise SkipTest #Skip this unconditionally for release 0.3.0 #since there are still problems with scipy 0.9.0 on some machines #Ralf on mailing list 2011-03-26 raise SkipTest data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog) res2 = Spector() res2.logit() cls.res2 = res2 cls.res1 = Logit(data.endog, data.exog).fit(method="bfgs", disp=0)
def setupClass(cls): # import scipy # major, minor, micro = scipy.__version__.split('.')[:3] # if int(minor) < 9: # raise SkipTest # Skip this unconditionally for release 0.3.0 # since there are still problems with scipy 0.9.0 on some machines # Ralf on mailing list 2011-03-26 raise SkipTest data = sm.datasets.spector.load() data.exog = sm.add_constant(data.exog) res2 = Spector() res2.logit() cls.res2 = res2 cls.res1 = Logit(data.endog, data.exog).fit(method="bfgs", disp=0)