5d8b81e16143d6eea9e86a586fe737854c03c772,linearmodels/tests/panel/test_panel_ols.py,,test_panel_time_lvsd_weighted,#Any#,475

Before Change


    res2 = ols_mod.fit("robust")
    assert_results_equal(res, res2, test_fit=False)

    clusters = mod.reformat_clusters(data.vc1)
    res = mod.fit(cov_type="clustered", clusters=clusters)
    res2 = ols_mod.fit("clustered", clusters=clusters.dataframe)
    assert_results_equal(res, res2, test_fit=False)

    clusters = mod.reformat_clusters(data.vc2)
    res = mod.fit(cov_type="clustered", clusters=clusters)
    res2 = ols_mod.fit("clustered", clusters=clusters.dataframe)
    assert_results_equal(res, res2, test_fit=False)

After Change




def test_panel_time_lvsd_weighted(data):
    mod = PanelOLS(data.y, data.x, time_effect=True, weights=data.w)
    res = mod.fit()

    y = mod.dependent.dataframe
    x = mod.exog.dataframe
    w = mod.weights.dataframe
    d = mod.dependent.dummies("time", drop_first=mod.has_constant)
    d_cols = d.columns
    d = d.values
    if mod.has_constant:
        z = np.ones_like(y)
        root_w = np.sqrt(w.values)
        wd = root_w * d
        wz = root_w * z
        d = d - z @ np.linalg.lstsq(wz, wd)[0]

    xd = np.c_[x.values, d]
    xd = pd.DataFrame(xd, index=x.index, columns=list(x.columns) + list(d_cols))

    ols_mod = IV2SLS(y, xd, None, None, weights=w)
    res2 = ols_mod.fit("unadjusted")
    assert_results_equal(res, res2, test_fit=False)

    res = mod.fit(cov_type="robust")
    res2 = ols_mod.fit("robust")
    assert_results_equal(res, res2, test_fit=False)

    clusters = data.vc1
    ols_clusters = mod.reformat_clusters(clusters)
    res = mod.fit(cov_type="clustered", clusters=clusters)
    res2 = ols_mod.fit("clustered", clusters=ols_clusters.dataframe)
    assert_results_equal(res, res2, test_fit=False)

    clusters = data.vc2
    ols_clusters = mod.reformat_clusters(clusters)
    res = mod.fit(cov_type="clustered", clusters=clusters)
    res2 = ols_mod.fit("clustered", clusters=ols_clusters.dataframe)
    assert_results_equal(res, res2, test_fit=False)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 6

Non-data size: 6

Instances


Project Name: bashtage/linearmodels
Commit Name: 5d8b81e16143d6eea9e86a586fe737854c03c772
Time: 2017-04-07
Author: kevin.k.sheppard@gmail.com
File Name: linearmodels/tests/panel/test_panel_ols.py
Class Name:
Method Name: test_panel_time_lvsd_weighted


Project Name: bashtage/linearmodels
Commit Name: 5d8b81e16143d6eea9e86a586fe737854c03c772
Time: 2017-04-07
Author: kevin.k.sheppard@gmail.com
File Name: linearmodels/tests/panel/test_panel_ols.py
Class Name:
Method Name: test_panel_both_lvsd


Project Name: bashtage/linearmodels
Commit Name: 5d8b81e16143d6eea9e86a586fe737854c03c772
Time: 2017-04-07
Author: kevin.k.sheppard@gmail.com
File Name: linearmodels/tests/panel/test_panel_ols.py
Class Name:
Method Name: test_panel_other_lvsd


Project Name: bashtage/linearmodels
Commit Name: 5d8b81e16143d6eea9e86a586fe737854c03c772
Time: 2017-04-07
Author: kevin.k.sheppard@gmail.com
File Name: linearmodels/tests/panel/test_panel_ols.py
Class Name:
Method Name: test_panel_time_lvsd


Project Name: bashtage/linearmodels
Commit Name: 5d8b81e16143d6eea9e86a586fe737854c03c772
Time: 2017-04-07
Author: kevin.k.sheppard@gmail.com
File Name: linearmodels/tests/panel/test_panel_ols.py
Class Name:
Method Name: test_panel_both_lvsd_weighted


Project Name: bashtage/linearmodels
Commit Name: 5d8b81e16143d6eea9e86a586fe737854c03c772
Time: 2017-04-07
Author: kevin.k.sheppard@gmail.com
File Name: linearmodels/tests/panel/test_panel_ols.py
Class Name:
Method Name: test_panel_time_lvsd_weighted


Project Name: bashtage/linearmodels
Commit Name: 5d8b81e16143d6eea9e86a586fe737854c03c772
Time: 2017-04-07
Author: kevin.k.sheppard@gmail.com
File Name: linearmodels/tests/panel/test_panel_ols.py
Class Name:
Method Name: test_panel_entity_lvsd_weighted