AttributeError: 'DecomposeResult' object has no attribute 'save'

[gsamaras]

Describe the bug

Unable to save an STL model. This Stack Overflow answer says that: "The models and results instances all have a save and load method, so you don't need to use the pickle module directly.".

Is that true or should I use the pickle module directly?

Code Sample, a copy-pastable example if possible

import statsmodels.api as sm
import matplotlib.pyplot as plt

result = STL(data, period=7).fit()
result.save("STL_model.pickle")

I get this error:

AttributeError: 'DecomposeResult' object has no attribute 'save'

Expected Output

A saved model.

Output of import statsmodels.api as sm; sm.show_versions()

INSTALLED VERSIONS

Python: 3.7.12.final.0
OS: Linux 5.10.90+ #1 SMP Wed Mar 23 09:10:07 UTC 2022 x86_64
byteorder: little
LC_ALL: C.UTF-8
LANG: C.UTF-8

statsmodels

Installed: 0.13.1 (/opt/conda/lib/python3.7/site-packages/statsmodels)

Required Dependencies

cython: 0.29.28 (/opt/conda/lib/python3.7/site-packages/Cython)
numpy: 1.20.3 (/opt/conda/lib/python3.7/site-packages/numpy)
scipy: 1.7.3 (/opt/conda/lib/python3.7/site-packages/scipy)
pandas: 1.3.5 (/opt/conda/lib/python3.7/site-packages/pandas)
dateutil: 2.8.2 (/opt/conda/lib/python3.7/site-packages/dateutil)
patsy: 0.5.2 (/opt/conda/lib/python3.7/site-packages/patsy)

Optional Dependencies

matplotlib: 3.5.1 (/opt/conda/lib/python3.7/site-packages/matplotlib)
backend: module://matplotlib_inline.backend_inline
cvxopt: Not installed
joblib: 1.1.0 (/opt/conda/lib/python3.7/site-packages/joblib)

Developer Tools

IPython: 7.30.1 (/opt/conda/lib/python3.7/site-packages/IPython)
jinja2: 3.0.3 (/opt/conda/lib/python3.7/site-packages/jinja2)
sphinx: Not installed
pygments: 2.10.0 (/opt/conda/lib/python3.7/site-packages/pygments)
pytest: 7.1.0 (/opt/conda/lib/python3.7/site-packages/pytest)
virtualenv: 20.10.0 (/opt/conda/lib/python3.7/site-packages/virtualenv)

[gsamaras]

OK I didn't think this through and I can't delete this issue. You don't save decomposition result, but the models you train on the components!