Change in behavior for rolling_var when win > len(arr) for 0.14: now raises error
In 0.13 I could pass a window length greater than the length of the `Series` passed to `rolling_var` (or, of course, `rolling_std`). In 0.14 that raises an error. Behavior is unchanged from 0.13 for other rolling functions:

``` python
data = """
x
0.1
0.5
0.3
0.2
0.7
"""

df = pd.read_csv(StringIO(data),header=True)

>>> pd.rolling_mean(df['x'],window=6,min_periods=2)

0      NaN
1    0.300
2    0.300
3    0.275
4    0.360
dtype: float64

>>> pd.rolling_skew(df['x'],window=6,min_periods=2)

0             NaN
1             NaN
2    3.903128e-15
3    7.528372e-01
4    6.013638e-01
dtype: float64

>>> pd.rolling_skew(df['x'],window=6,min_periods=6)

0   NaN
1   NaN
2   NaN
3   NaN
4   NaN
dtype: float64
```

Those work, but not `rolling_var`:

``` python
>>> pd.rolling_var(df['x'],window=6,min_periods=2)

Traceback (most recent call last):
  File "./foo.py", line 187, in <module>
    print pd.rolling_var(df['x'],window=6,min_periods=2)
  File "/usr/lib64/python2.7/site-packages/pandas/stats/moments.py", line 594, in f
    center=center, how=how, **kwargs)
  File "/usr/lib64/python2.7/site-packages/pandas/stats/moments.py", line 346, in _rolling_moment
    result = calc(values)
  File "/usr/lib64/python2.7/site-packages/pandas/stats/moments.py", line 340, in <lambda>
    **kwds)
  File "/usr/lib64/python2.7/site-packages/pandas/stats/moments.py", line 592, in call_cython
    return func(arg, window, minp, **kwds)
  File "algos.pyx", line 1177, in pandas.algos.roll_var (pandas/algos.c:28449)
IndexError: Out of bounds on buffer access (axis 0)
```

If this is the new desired default behavior for the rolling functions, I can work around it. I do like the behavior of `rolling_skew` and `rolling_mean` better. It was nice default behavior for me when I was doing rolling standard deviations for reasonably large financial data panels.

It looks to me like the issue is caused by the fact that the 0.14 algo for rolling variance is implemented such that the initial loop (`roll_var` (algos.pyx))  is the following:

``` python
for i from 0 <= i < win:
```

So it loops to `win` even when `win > N`. 

It looks like to me that the other rolling functions try to implement their algos in such a way that the first loop counts over the following:

``` python
for i from 0 <= i < minp - 1:
```

``` python
>>> pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.5.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.10-200.fc20.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.14.0
nose: 1.3.1
Cython: 0.20.1
numpy: 1.8.1
scipy: 0.13.3
statsmodels: 0.6.0.dev-b52bc09
IPython: 2.0.0
sphinx: 1.2.2
patsy: 0.2.1
scikits.timeseries: None
dateutil: 2.2
pytz: 2014.3
bottleneck: 0.8.0
tables: None
numexpr: 2.4
matplotlib: 1.3.1
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: 0.7.5
xlsxwriter: 0.5.3
lxml: 3.3.5
bs4: 4.3.2
html5lib: 0.999
bq: None
apiclient: None
rpy2: None
sqlalchemy: 0.9.4
pymysql: None
psycopg2: None
Non
```

Karl D.
