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Python MLEModel.ssm['selection',0,0]方法代码示例

本文整理汇总了Python中statsmodels.tsa.statespace.mlemodel.MLEModel.ssm['selection',0,0]方法的典型用法代码示例。如果您正苦于以下问题:Python MLEModel.ssm['selection',0,0]方法的具体用法?Python MLEModel.ssm['selection',0,0]怎么用?Python MLEModel.ssm['selection',0,0]使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在statsmodels.tsa.statespace.mlemodel.MLEModel的用法示例。


在下文中一共展示了MLEModel.ssm['selection',0,0]方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: test_diagnostics_nile_durbinkoopman

# 需要导入模块: from statsmodels.tsa.statespace.mlemodel import MLEModel [as 别名]
# 或者: from statsmodels.tsa.statespace.mlemodel.MLEModel import ssm['selection',0,0] [as 别名]
def test_diagnostics_nile_durbinkoopman():
    # Test the diagnostic tests using the Nile dataset. Results are from 
    # Durbin and Koopman (2012); parameter values reported on page 37; test
    # statistics on page 40
    niledata = nile.data.load_pandas().data
    niledata.index = pd.date_range('1871-01-01', '1970-01-01', freq='AS')

    mod = MLEModel(niledata['volume'], k_states=1,
        initialization='approximate_diffuse', initial_variance=1e15,
        loglikelihood_burn=1)
    mod.ssm['design', 0, 0] = 1
    mod.ssm['obs_cov', 0, 0] = 15099.
    mod.ssm['transition', 0, 0] = 1
    mod.ssm['selection', 0, 0] = 1
    mod.ssm['state_cov', 0, 0] = 1469.1
    res = mod.filter([])

    # Test Ljung-Box
    # Note: only 3 digits provided in the reference paper
    actual = res.test_serial_correlation(method='ljungbox', lags=9)[0, 0, -1]
    assert_allclose(actual, [8.84], atol=1e-2)

    # Test Jarque-Bera
    # Note: The book reports 0.09 for Kurtosis, because it is reporting the
    # statistic less the mean of the Kurtosis distribution (which is 3).
    norm = res.test_normality(method='jarquebera')[0]
    actual = [norm[0], norm[2], norm[3]]
    assert_allclose(actual, [0.05, -0.03, 3.09], atol=1e-2)

    # Test Heteroskedasticity
    # Note: only 2 digits provided in the book
    actual = res.test_heteroskedasticity(method='breakvar')[0, 0]
    assert_allclose(actual, [0.61], atol=1e-2)
开发者ID:edhuckle,项目名称:statsmodels,代码行数:35,代码来源:test_mlemodel.py

示例2: test_diagnostics_nile_eviews

# 需要导入模块: from statsmodels.tsa.statespace.mlemodel import MLEModel [as 别名]
# 或者: from statsmodels.tsa.statespace.mlemodel.MLEModel import ssm['selection',0,0] [as 别名]
def test_diagnostics_nile_eviews():
    # Test the diagnostic tests using the Nile dataset. Results are from 
    # "Fitting State Space Models with EViews" (Van den Bossche 2011,
    # Journal of Statistical Software).
    # For parameter values, see Figure 2
    # For Ljung-Box and Jarque-Bera statistics and p-values, see Figure 5
    # The Heteroskedasticity statistic is not provided in this paper.
    niledata = nile.data.load_pandas().data
    niledata.index = pd.date_range('1871-01-01', '1970-01-01', freq='AS')

    mod = MLEModel(niledata['volume'], k_states=1,
        initialization='approximate_diffuse', initial_variance=1e15,
        loglikelihood_burn=1)
    mod.ssm['design', 0, 0] = 1
    mod.ssm['obs_cov', 0, 0] = np.exp(9.600350)
    mod.ssm['transition', 0, 0] = 1
    mod.ssm['selection', 0, 0] = 1
    mod.ssm['state_cov', 0, 0] = np.exp(7.348705)
    res = mod.filter([])

    # Test Ljung-Box
    # Note: only 3 digits provided in the reference paper
    actual = res.test_serial_correlation(method='ljungbox', lags=10)[0, :, -1]
    assert_allclose(actual, [13.117, 0.217], atol=1e-3)

    # Test Jarque-Bera
    actual = res.test_normality(method='jarquebera')[0, :2]
    assert_allclose(actual, [0.041686, 0.979373], atol=1e-5)
开发者ID:edhuckle,项目名称:statsmodels,代码行数:30,代码来源:test_mlemodel.py


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