def __init__(self,
data,
lag_order=1,
window=None,
window_type='expanding',
trend='c',
min_periods=None):
require_pandas()
self.lag_order = lag_order
self.names = list(data.columns)
self.neqs = len(self.names)
self._y_orig = data
# TODO: deal with trend
self._x_orig = _make_lag_matrix(data, lag_order)
self._x_orig['intercept'] = 1
(self.y, self.x, self.x_filtered, self._index,
self._time_has_obs) = _filter_data(self._y_orig, self._x_orig)
self.lag_order = lag_order
self.trendorder = util.get_trendorder(trend)
self._set_window(window_type, window, min_periods)
def __init__(self, data, lag_order=1, window=None, window_type="expanding", trend="c", min_periods=None):
self.lag_order = lag_order
self.neqs = len(data.columns)
self._y_orig = data
# TODO: deal with trend
self._x_orig = _make_lag_matrix(data, lag_order)
self._x_orig["intercept"] = 1
(self.y, self.x, self.x_filtered, self._index, self._time_has_obs) = _filter_data(self._y_orig, self._x_orig)
self.lag_order = lag_order
self.trendorder = util.get_trendorder(trend)
self._set_window(window_type, window, min_periods)
def __init__(self, data, lag_order=1, window=None, window_type='expanding',
trend='c', min_periods=None):
require_pandas()
self.lag_order = lag_order
self.names = list(data.columns)
self.neqs = len(self.names)
self._y_orig = data
# TODO: deal with trend
self._x_orig = _make_lag_matrix(data, lag_order)
self._x_orig['intercept'] = 1
(self.y, self.x, self.x_filtered, self._index,
self._time_has_obs) = _filter_data(self._y_orig, self._x_orig)
self.lag_order = lag_order
self.trendorder = util.get_trendorder(trend)
self._set_window(window_type, window, min_periods)