Different behavior of DataFrame.resample() between pandas 0.16.2 and pandas 0.18.1
I just upgraded my projects from pandas 0.16.2 to pandas 0.18.1, but I have a difference on some `DataFrame.resample` operations, with Weekly frequencies.

For instance, I want to resample daily data to weekly data (`W-SUN`), and apply an offset to the results, so each row will be a **MONDAY** and not a SUNDAY.

#### Code Sample

```python
import pandas as pd
from datetime import timedelta
offset = +timedelta(days=1)

dates = pd.date_range("2001-01-01", freq="D", periods=18)]
a=pd.DataFrame(data=list(range(18)), columns=["value"], index=[dates])

a.resample("1W", how={"value": "sum"}, loffset=offset, closed="right", label="right")
```
#### Problem description

With `pandas 0.16.2`, I got this correct output:
```
            value
2001-01-08     21
2001-01-15     70
2001-01-22     62
```
ie, each row is a weekly aggregation of the data, and each date is a **MONDAY**

Resulting index is as follow:
```
a.index[0]
Timestamp('2001-01-08 00:00:00', offset='W-MON')
```

However, with `pandas 0.18.1`, I got this output:
```
            value
2001-01-07     21
2001-01-14     70
2001-01-21     62
```
each row is correctly aggregated, but the dates are **SUNDAY**s

Resulting index is as follow:
```
a.index[0]
Timestamp('2001-01-07 00:00:00', offset='W-SUN')
```

<observations>

It's like the `loffset` parameter is not correctly taken into account in  the new `DataFrame.resample()` implementation.

ie, the output with `pandas 0.18.1` is the same as the one using `pandas 0.16.2`, but calling `a.resample("1W", how={"value": "sum"}, `**loffset=None**`, closed="right", label="right")`

</observations>

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

pandas `0.16.1` installation:

<details>

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.5.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-106-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.16.2
nose: 1.3.7
Cython: 0.22.1
numpy: 1.10.1
scipy: 0.16.0
statsmodels: 0.6.1
IPython: 3.2.1
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.7
bottleneck: 1.0.0
tables: 3.2.1
numexpr: 2.4.3
matplotlib: 1.5.0
openpyxl: 2.3.2
xlrd: 0.9.3
xlwt: 1.0.0
xlsxwriter: 0.7.3
lxml: 3.4.4
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.7
pymysql: 0.6.6.None
psycopg2: None
```

</details>

pandas `0.18.2` installation:
<details>

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.5.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-57-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.22.1
numpy: 1.10.4
scipy: 0.16.0
statsmodels: 0.6.1
xarray: None
IPython: 3.2.1
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.6
blosc: None
bottleneck: 1.0.0
tables: 3.2.1
numexpr: 2.6.0
matplotlib: 1.4.3
openpyxl: 2.3.2
xlrd: 0.9.3
xlwt: 1.0.0
xlsxwriter: 0.7.3
lxml: 3.4.4
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.7
pymysql: 0.6.6.None
psycopg2: None
jinja2: 2.7.3
boto: None
pandas_datareader: None
```
</details>
