Apply not available for all windows type
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np
df = pd.DataFrame({'A': range(1000)})
df.rolling(5, center=True, win_type='triang').apply(lambda x: np.nanstd(x), raw=False)
```
#### Problem description
The above produces an error, stating that the `Window` class produces by the rolling function does not have an `apply` attribute.

If I remove the `win_type` attribute, the computation goes fine and returns a result:
```
	A
0	NaN
1	NaN
2	1.414214
3	1.414214
4	1.414214
...	...
995	1.414214
996	1.414214
997	1.414214
998	NaN
999	NaN
```

#### Expected Output
I expect the `apply` attribute to be available to any `win_type` (I did not see any restrictions in the documentation of `pd.DataFrame.rolling` (https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rolling.html), or the documentation of `pd.DataFrame.rolling.apply` (https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.window.Rolling.apply.html))

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.8.final.0
python-bits      : 64
OS               : Windows
OS-release       : 7
machine          : AMD64
processor        : Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : fr_FR.UTF-8
LOCALE           : None.None

pandas           : 0.25.1
numpy            : 1.16.2
pytz             : 2018.9
dateutil         : 2.8.0
pip              : 19.1.1
setuptools       : 40.8.0
Cython           : 0.29.6
pytest           : 4.3.1
hypothesis       : None
sphinx           : 1.8.5
blosc            : None
feather          : None
xlsxwriter       : 1.1.5
lxml.etree       : 4.3.2
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.10
IPython          : 7.4.0
pandas_datareader: None
bs4              : 4.7.1
bottleneck       : 1.2.1
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.3.2
matplotlib       : 3.0.3
numexpr          : 2.6.9
odfpy            : None
openpyxl         : 2.6.1
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : 1.2.1
sqlalchemy       : 1.3.1
tables           : 3.5.1
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.1.5

</details>
