'collect required results from the LOOO loop
all results will be attached.
currently only \'params\', \'mse_resid\', \'det_cov_params\' are stored
regresses endog on exog dropping one observation at a time
this uses a nobs loop, only attributes of the OLS instance are stored.'

@cache_readonly
def _res_looo(self):

    from statsmodels.sandbox.tools.cross_val import LeaveOneOut
    get_det_cov_params = (lambda res: np.linalg.det(res.cov_params()))
    endog = self.endog
    exog = self.exog
    params = np.zeros(exog.shape, dtype=np.float)
    mse_resid = np.zeros(endog.shape, dtype=np.float)
    det_cov_params = np.zeros(endog.shape, dtype=np.float)
    cv_iter = LeaveOneOut(self.nobs)
    for (inidx, outidx) in cv_iter:
        res_i = self.model_class(endog[inidx], exog[inidx]).fit()
        params[outidx] = res_i.params
        mse_resid[outidx] = res_i.mse_resid
        det_cov_params[outidx] = get_det_cov_params(res_i)
    return dict(params=params, mse_resid=mse_resid, det_cov_params=det_cov_params)
