pandas.DataFrame.rolling should accept Timedelta not DateOffset
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
index=pd.date_range("2019-01-01-05:00:00", freq="B", periods=10)
x = pd.Series(1., index)
dt = Timedelta("2D")
x.rolling(dt).sum()
2001-01-01    1.0
2001-01-02    2.0
2001-01-03    2.0
2001-01-04    2.0
2001-01-05    2.0
2001-01-08    1.0
2001-01-09    2.0
2001-01-10    2.0
2001-01-11    2.0
2001-01-12    2.0
Freq: B, dtype: float64

x.rolling("B").sum()
...
ValueError: <BusinessDay> is a non-fixed frequency
```
#### Problem description

The documentation states that rolling can be used with `DateOffset`. In fact it can only be used with fixed freq DateOffsets, usage with non-fixed freq DateOffsets will raise. If I get it correctly all
fixed freq DateOffsets can be represented as `Timedelta` instances? Wouldn't it make sense to allow only `Timedelta` instead of DateOffset for rolling operations. 

Apologies, if I am missing a case where a fixed freq `DateOffset` cannot be expressed as a `Timedelta`. In any case the documentation should be more explicit about the admissible `DateOffsets`

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

<details>
INSTALLED VERSIONS
------------------
commit: None

pandas: 0.23.4
pytest: None
pip: 10.0.1
setuptools: 39.2.0
Cython: None
numpy: 1.15.4
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.5.0
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None/details>
