Methods min and max give NaN in time-aware rolling window even if min_periods=1
#### Code Sample, a copy-pastable example if possible

```python
df = pd.DataFrame({'a': [None, 2, 3]}, index=pd.to_datetime(['20170403', '20170404', '20170405']))

df.rolling('3d', min_periods=1)['a'].sum()

df.rolling('3d', min_periods=1)['a'].min()
df.rolling('3d', min_periods=1)['a'].max()
```
#### Problem description
Even if we set `min_periods=1`, the functions `min` and `max` give NaN if there is one NaN value inside the time-aware rolling window.

However, there is no bug when the window width is fixed (not a time period):
```javascript
In [397]: df.rolling(3, min_periods=1)['a'].min()
Out[397]:
2017-04-03    NaN
2017-04-04    2.0
2017-04-05    2.0
Name: a, dtype: float64
```

#### Expected Output
The expected output, analogously to the one given by the function `sum`, should be a non-NaN value if at least there is a non-NaN value inside the rolling window.

```javascript
In [397]: df.rolling('3d', min_periods=1)['a'].min()
Out[397]:
2017-04-03    NaN
2017-04-04    2.0
2017-04-05    2.0
Name: a, dtype: float64

In [397]: df.rolling('3d', min_periods=1)['a'].min()
Out[397]:
2017-04-03    NaN
2017-04-04    2.0
2017-04-05    3.0
Name: a, dtype: float64
```

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

<details>
commit: None
python: 3.4.5.final.0
python-bits: 64
OS: Linux
OS-release: 2.6.32-431.29.2.el6.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: C
LOCALE: None.None

pandas: 0.19.2
nose: 1.3.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.11.3
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.0
tables: 3.3.0
numexpr: 2.6.1
matplotlib: 1.5.1
openpyxl: 2.4.0
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.6
lxml: 3.7.2
bs4: 4.5.3
html5lib: None
httplib2: 0.9.2
apiclient: None
sqlalchemy: 1.1.4
pymysql: None
psycopg2: None
jinja2: 2.8.1
boto: 2.45.0
pandas_datareader: None
</details>
