def test_compare(data, stars): res1 = IV2SLS(data.dep, data.exog, data.endog, data.instr).fit() res2 = IV2SLS(data.dep, data.exog, data.endog, data.instr[:, :-1]).fit() res3 = IVGMM(data.dep, data.exog[:, :2], data.endog, data.instr).fit() res4 = IV2SLS(data.dep, data.exog, data.endog, data.instr).fit() c = compare([res1, res2, res3, res4], stars=stars) assert len(c.rsquared) == 4 assert isinstance(str(c.summary), str) if stars: total = 1 * (c.pvalues < 0.10) + (c.pvalues < 0.05) + (c.pvalues < 0.01) total_stars = np.asarray(total).sum() count = sum([char == "*" for char in str(c.summary)]) print(c.pvalues) print(total) print(c.summary) assert count == total_stars c = compare({ "Model A": res1, "Model B": res2, "Model C": res3, "Model D": res4 }) assert isinstance(str(c.summary), str) res = {"Model A": res1, "Model B": res2, "Model C": res3, "Model D": res4} c = compare(res, stars=stars) assert isinstance(str(c.summary), str) assert isinstance(c.pvalues, pd.DataFrame) res1 = IV2SLS(data.dep, data.exog[:, :1], None, None).fit() res2 = IV2SLS(data.dep, data.exog[:, :2], None, None).fit() c = compare({"Model A": res1, "Model B": res2}, stars=stars) assert isinstance(str(c.summary), str)
def test_compare(data): res1 = IV2SLS(data.dep, data.exog, data.endog, data.instr).fit() res2 = IV2SLS(data.dep, data.exog, data.endog, data.instr[:, :-1]).fit() res3 = IVGMM(data.dep, data.exog[:, :2], data.endog, data.instr).fit() res4 = IV2SLS(data.dep, data.exog, data.endog, data.instr).fit() c = compare([res1, res2, res3, res4]) assert len(c.rsquared) == 4 c.summary c = compare({ 'Model A': res1, 'Model B': res2, 'Model C': res3, 'Model D': res4 }) c.summary res = OrderedDict() res['Model A'] = res1 res['Model B'] = res2 res['Model C'] = res3 res['Model D'] = res4 c = compare(res) c.summary c.pvalues res1 = IV2SLS(data.dep, data.exog[:, :1], None, None).fit() res2 = IV2SLS(data.dep, data.exog[:, :2], None, None).fit() c = compare({'Model A': res1, 'Model B': res2}) c.summary
def test_compare_single(data): res1 = IV2SLS(data.dep, data.exog, data.endog, data.instr).fit() c = compare([res1]) assert len(c.rsquared) == 1 c.summary c = compare({"Model A": res1}) c.summary res = {"Model A": res1} c = compare(res) c.summary c.pvalues
def test_compare_single(data): res1 = IV2SLS(data.dep, data.exog, data.endog, data.instr).fit() c = compare([res1]) assert len(c.rsquared) == 1 assert isinstance(c.summary, Summary) c = compare({"Model A": res1}) assert isinstance(c.summary, Summary) res = {"Model A": res1} c = compare(res) assert isinstance(c.summary, Summary) assert isinstance(c.pvalues, pd.DataFrame)
def test_compare_single(data): res1 = IV2SLS(data.dep, data.exog, data.endog, data.instr).fit() c = compare([res1]) assert len(c.rsquared) == 1 c.summary c = compare({'Model A': res1}) c.summary res = OrderedDict() res['Model A'] = res1 c = compare(res) c.summary c.pvalues
def test_compare(data): res1 = IV2SLS(data.dep, data.exog, data.endog, data.instr).fit() res2 = IV2SLS(data.dep, data.exog, data.endog, data.instr[:, :-1]).fit() res3 = IVGMM(data.dep, data.exog[:, :2], data.endog, data.instr).fit() res4 = IV2SLS(data.dep, data.exog, data.endog, data.instr).fit() c = compare([res1, res2, res3, res4]) assert len(c.rsquared) == 4 c.summary c = compare({ "Model A": res1, "Model B": res2, "Model C": res3, "Model D": res4 }) c.summary res = {"Model A": res1, "Model B": res2, "Model C": res3, "Model D": res4} c = compare(res) c.summary c.pvalues res1 = IV2SLS(data.dep, data.exog[:, :1], None, None).fit() res2 = IV2SLS(data.dep, data.exog[:, :2], None, None).fit() c = compare({"Model A": res1, "Model B": res2}) c.summary
def test_compare_single_single_parameter(data): res1 = IV2SLS(data.dep, data.exog[:, :1], None, None).fit() c = compare([res1]) assert len(c.rsquared) == 1 c.summary