from statsmodels.tools.decorators import cache_readonly
import statsmodels.base.wrapper as wrap
from statsmodels.compat.pandas import Appender
+import platform
+import warnings
+warn_dfactor_platform= "DynamicFactor can give wrong results on ppc64el" if platform.uname()[4].startswith('ppc') else False # test results at end of https://buildd.debian.org/status/fetch.php?pkg=statsmodels&arch=ppc64el&ver=0.11.0-1&stamp=1580692747&raw=0
class DynamicFactor(MLEModel):
def __init__(self, endog, k_factors, factor_order, exog=None,
error_order=0, error_var=False, error_cov_type='diagonal',
enforce_stationarity=True, **kwargs):
+ if warn_dfactor_platform:
+ warnings.warn(warn_dfactor_platform)
# Model properties
self.enforce_stationarity = enforce_stationarity
import warnings
import numpy as np
+from statsmodels.tsa.statespace.dynamic_factor import warn_dfactor_platform
from numpy.testing import assert_equal, assert_raises, assert_allclose
import pandas as pd
import pytest
r'cov.chol\[3,3\] +' + forg(params[offset + 5], prec=4),
table)
-
+@pytest.mark.xfail(condition=bool(warn_dfactor_platform),reason='known broken on ppc64el',strict=False)
class TestDynamicFactor_ar2_errors(CheckDynamicFactor):
"""
Test for a dynamic factor model where errors are as general as possible,