Python parse_lutkepohl_data Examples

Example #1

File: var_model.py Project: chrisjordansquire/statsmodels

        result.append(r)

    return np.array(result) / len(x)

def _acovs_to_acorrs(acovs):
    sd = np.sqrt(np.diag(acovs[0]))
    return acovs / np.outer(sd, sd)

if __name__ == '__main__':
    import scikits.statsmodels.api as sm
    from scikits.statsmodels.tsa.vector_ar.util import parse_lutkepohl_data
    import scikits.statsmodels.tools.data as data_util

    np.set_printoptions(linewidth=140, precision=5)

    sdata, dates = parse_lutkepohl_data('data/%s.dat' % 'e1')

    names = sdata.dtype.names
    data = data_util.struct_to_ndarray(sdata)
    adj_data = np.diff(np.log(data), axis=0)
    # est = VAR(adj_data, p=2, dates=dates[1:], names=names)
    model = VAR(adj_data[:-16], dates=dates[1:-16], names=names)
    # model = VAR(adj_data[:-16], dates=dates[1:-16], names=names)

    est = model.fit(maxlags=2)
    irf = est.irf()

    y = est.y[-2:]
    """
    # irf.plot_irf()

Example #2

File: test_var.py Project: chrisjordansquire/statsmodels

def get_lutkepohl_data(name='e2'):
    lut_data = basepath + '/tsa/vector_ar/data/'
    path = lut_data + '%s.dat' % name

    return util.parse_lutkepohl_data(path)

Example #3

File: test_var.py Project: Creamery/OOTO-Miner-V5

def get_lutkepohl_data(name='e2'):
    lut_data = basepath + '/tsa/vector_ar/data/'
    path = lut_data + '%s.dat' % name

    return util.parse_lutkepohl_data(path)

Example #4

    return np.array(result) / len(x)


def _acovs_to_acorrs(acovs):
    sd = np.sqrt(np.diag(acovs[0]))
    return acovs / np.outer(sd, sd)


if __name__ == '__main__':
    import scikits.statsmodels.api as sm
    from scikits.statsmodels.tsa.vector_ar.util import parse_lutkepohl_data
    import scikits.statsmodels.tools.data as data_util

    np.set_printoptions(linewidth=140, precision=5)

    sdata, dates = parse_lutkepohl_data('data/%s.dat' % 'e1')

    names = sdata.dtype.names
    data = data_util.struct_to_ndarray(sdata)
    adj_data = np.diff(np.log(data), axis=0)
    # est = VAR(adj_data, p=2, dates=dates[1:], names=names)
    model = VAR(adj_data[:-16], dates=dates[1:-16], names=names)
    # model = VAR(adj_data[:-16], dates=dates[1:-16], names=names)

    est = model.fit(maxlags=2)
    irf = est.irf()

    y = est.y[-2:]
    """
    # irf.plot_irf()