def test_more_than_one_glm_is_ok(self):
with Model():
GLM.from_formula('y ~ x', self.data_logistic,
family=families.Binomial(link=families.logit),
name='glm1')
GLM.from_formula('y ~ x', self.data_logistic,
family=families.Binomial(link=families.logit),
name='glm2')
def test_from_xy(self):
with Model():
GLM(
self.data_logistic["x"],
self.data_logistic["y"],
family=families.Binomial(link=families.logit),
name="glm1",
)
def test_glm_link_func2(self):
with Model() as model:
GLM.from_formula('y ~ x', self.data_logistic2,
family=families.Binomial(priors={'n': self.data_logistic2['n']}))
trace = sample(1000, progressbar=False, init='adapt_diag',
random_seed=self.random_seed)
assert round(abs(np.mean(trace['Intercept'])-self.intercept), 1) == 0
assert round(abs(np.mean(trace['x'])-self.slope), 1) == 0
def test_glm_link_func(self):
with Model() as model:
GLM.from_formula('y ~ x', self.data_logistic,
family=families.Binomial(link=families.logit))
step = Slice(model.vars)
trace = sample(1000, step, progressbar=False, random_seed=self.random_seed)
assert round(abs(np.mean(trace['Intercept'])-self.intercept), 1) == 0
assert round(abs(np.mean(trace['x'])-self.slope), 1) == 0
def test_glm_link_func2(self):
with Model() as model:
GLM.from_formula(
"y ~ x",
self.data_logistic2,
family=families.Binomial(priors={"n": self.data_logistic2["n"]}),
)
trace = sample(1000, progressbar=False, init="adapt_diag", random_seed=self.random_seed)
assert round(abs(np.mean(trace["Intercept"]) - self.intercept), 1) == 0
assert round(abs(np.mean(trace["x"]) - self.slope), 1) == 0
def test_from_xy(self):
with Model():
GLM(self.data_logistic['x'],
self.data_logistic['y'],
family=families.Binomial(link=families.logit),
name='glm1')
