test_against_stata.py 文件源码

def construct_model(key):
    model, nendog, nexog, ninstr, weighted, var, other = key.split('-')
    var = var.replace('wmatrix', 'vce')
    mod = MODELS[model]
    data = SIMULATED_DATA
    endog = data[['x1', 'x2']] if '2' in nendog else data.x1
    exog = data[['x3', 'x4', 'x5']]
    instr = data[['z1', 'z2']] if '2' in ninstr else data.z1
    deps = {'vce(unadjusted)': data.y_unadjusted,
            'vce(robust)': data.y_robust,
            'vce(cluster cluster_id)': data.y_clustered,
            'vce(hac bartlett 12)': data.y_kernel}
    dep = deps[var]
    if 'noconstant' not in other:
        exog = sm.add_constant(data[['x3', 'x4', 'x5']])

    cov_opts = deepcopy(SIMULATED_COV_OPTIONS[var])
    cov_opts['debiased'] = 'small' in other
    mod_options = {}
    if 'True' in weighted:
        mod_options['weights'] = data.weights
    if model == 'gmm':
        mod_options.update(deepcopy(SIMULATED_COV_OPTIONS[var]))
        mod_options['weight_type'] = mod_options['cov_type']
        del mod_options['cov_type']
        mod_options['center'] = 'center' in other

    model_result = mod(dep, exog, endog, instr, **mod_options).fit(**cov_opts)
    if model == 'gmm' and 'True' in weighted:
        pytest.skip('Weighted GMM differs slightly')
    return model_result