TST: copy ex_random_panel as test file

statsmodels/sandbox/panel/tests/test_random_panel.py

@@ -0,0 +1,104 @@
+# -*- coding: utf-8 -*-
+"""
+
+Created on Fri May 18 13:05:47 2012
+
+Author: Josef Perktold
+
+moved example from main of random_panel
+"""
+
+import numpy as np
+from statsmodels.sandbox.panel.panel_short import ShortPanelGLS, ShortPanelGLS2
+from statsmodels.sandbox.panel.random_panel import PanelSample
+import statsmodels.sandbox.panel.correlation_structures as cs
+
+
+examples = ['ex1']
+
+
+if 'ex1' in examples:
+    nobs = 100
+    nobs_i = 5
+    n_groups = nobs // nobs_i
+    k_vars = 3
+
+#    dgp = PanelSample(nobs, k_vars, n_groups, corr_structure=cs.corr_equi,
+#                      corr_args=(0.6,))
+#    dgp = PanelSample(nobs, k_vars, n_groups, corr_structure=cs.corr_ar,
+#                      corr_args=([1, -0.95],))
+    dgp = PanelSample(nobs, k_vars, n_groups, corr_structure=cs.corr_arma,
+                      corr_args=([1], [1., -0.9],), seed=377769)
+    print 'seed', dgp.seed
+    y = dgp.generate_panel()
+    noise = y - dgp.y_true
+    print np.corrcoef(y.reshape(-1,n_groups, order='F'))
+    print np.corrcoef(noise.reshape(-1,n_groups, order='F'))
+
+    mod = ShortPanelGLS2(y, dgp.exog, dgp.groups)
+    res = mod.fit()
+    print res.params
+    print res.bse
+    #Now what?
+    #res.resid is of transformed model
+    #np.corrcoef(res.resid.reshape(-1,n_groups, order='F'))
+    y_pred = np.dot(mod.exog, res.params)
+    resid = y - y_pred
+    print np.corrcoef(resid.reshape(-1,n_groups, order='F'))
+    print resid.std()
+    err = y_pred - dgp.y_true
+    print err.std()
+    #OLS standard errors are too small
+    mod.res_pooled.params
+    mod.res_pooled.bse
+    #heteroscedasticity robust doesn't help
+    mod.res_pooled.HC1_se
+    #compare with cluster robust se
+    import statsmodels.stats.sandwich_covariance as sw
+    print sw.se_cov(sw.cov_cluster(mod.res_pooled, dgp.groups.astype(int)))
+    #not bad, pretty close to panel estimator
+    #and with Newey-West Hac
+    print sw.se_cov(sw.cov_nw_panel(mod.res_pooled, 4, mod.group.groupidx))
+    #too small, assuming no bugs,
+    #see Peterson assuming it refers to same kind of model
+    print dgp.cov
+
+    mod2 = ShortPanelGLS(y, dgp.exog, dgp.groups)
+    res2 = mod2.fit_iterative(2)
+    print res2.params
+    print res2.bse
+    #both implementations produce the same results:
+    from numpy.testing import assert_almost_equal
+    assert_almost_equal(res.params, res2.params, decimal=14)
+    assert_almost_equal(res.bse, res2.bse, decimal=14)
+    mod5 = ShortPanelGLS(y, dgp.exog, dgp.groups)
+    res5 = mod5.fit_iterative(5)
+    print res5.params
+    print res5.bse
+    #fitting once is the same as OLS
+    #note: I need to create new instance, otherwise it continuous fitting
+    mod1 = ShortPanelGLS(y, dgp.exog, dgp.groups)
+    res1 = mod1.fit_iterative(1)
+    res_ols = mod1._fit_ols()
+    assert_almost_equal(res1.params, res_ols.params, decimal=14)
+    assert_almost_equal(res1.bse, res_ols.bse, decimal=14)
+
+    import pandas as pa
+    #pandas.DataFrame doesn't do inplace append
+    se = pa.DataFrame(res_ols.bse[None,:], index=['OLS'])
+    se = se.append(pa.DataFrame(res5.bse[None,:], index=['PGLSit5']))
+    clbse = sw.se_cov(sw.cov_cluster(mod.res_pooled, dgp.groups.astype(int)))
+    se = se.append(pa.DataFrame(clbse[None,:], index=['OLSclu']))
+    pnwse = sw.se_cov(sw.cov_nw_panel(mod.res_pooled, 4, mod.group.groupidx))
+    se = se.append(pa.DataFrame(pnwse[None,:], index=['OLSpnw']))
+    print se
+    #list(se.index)
+    from statsmodels.iolib.table import SimpleTable
+    headers = [str(i) for i in se.columns]
+    stubs=list(se.index)
+#    print SimpleTable(np.round(np.asarray(se), 4),
+#                      headers=headers,
+#                      stubs=stubs)
+    print SimpleTable(np.asarray(se), headers=headers, stubs=stubs,
+                      txt_fmt=dict(data_fmts=['%10.4f']),
+                      title='Standard Errors')