Exact matches in time-based .rolling()
I would like to `allow_exact_matches` in time-based `.rolling()`. Using an example similar to the one found in the documentation:

```
df = pd.DataFrame({'B': [1, 1, 2, np.nan, 4]},
                  index = [pd.Timestamp('20130101 09:00:00'),
                           pd.Timestamp('20130101 09:00:02'),
                           pd.Timestamp('20130101 09:00:03'),
                           pd.Timestamp('20130101 09:00:05'),
                           pd.Timestamp('20130101 09:00:06')])
```

I can compute the three-second rolling sum:

```
In [200]: df
Out[200]:
                       B
2013-01-01 09:00:00  1.0
2013-01-01 09:00:02  1.0
2013-01-01 09:00:03  2.0
2013-01-01 09:00:05  NaN
2013-01-01 09:00:06  4.0

In [201]: df.rolling('3s').sum()
Out[201]:
                       B
2013-01-01 09:00:00  1.0
2013-01-01 09:00:02  2.0
2013-01-01 09:00:03  3.0
2013-01-01 09:00:05  2.0
2013-01-01 09:00:06  4.0
```

But note that `09:00:03` does not include `09:00:00`, `09:00:05` does not include `09:00:02`, and `09:00:06` does not include `09:00:03`. If I were to include these timestamps, then I would have:

```
                       B
2013-01-01 09:00:00  1.0
2013-01-01 09:00:02  2.0
2013-01-01 09:00:03  4.0
2013-01-01 09:00:05  3.0
2013-01-01 09:00:06  6.0
```

A quick-and-dirty way of getting these values is with:

```
from itertools import starmap

window = pd.Timedelta('3s')

begins = np.searchsorted(df.index, df.index - window)
ends = np.arange(len(df)) + 1
ranges = starmap(range, zip(begins, ends))

pd.concat([df.ix[r].sum() for r in ranges])
```

`pd.merge_asof()` has the parameter `allow_exact_matches` to permit this. Would it be possible to add this to `.rolling()`?

I can try this one myself.
