[Mne_analysis] mne.stats.linear_regression
Emma Chen
emma.chen.w at nyu.edu
Fri Dec 2 05:03:03 EST 2016
Hi Mne users,
Is there a way to use mne.stats.linear_regression on epoch data or stc
data with *binary/categorical* predictors?
In the MEG data I'm analyzing, the regressor I would like to use is a
categorical variable with 4 different categories of objects indicating
which type of object participants saw in each trial.
I've tried to create the design_matrix with a column of intercept + 4
column of dummy variables for each category. But it didn't work. Following
is the error messages I got:
---------------------------------------------------------------------------
LinAlgError Traceback (most recent call last)
<ipython-input-49-728b72ea06ce> in <module>()
----> 1 res=mne.stats.linear_regression(epochs_ALL, design_matrix, names)
/Users/wc47/anaconda/envs/mne-python/lib/python2.7/site-packages/mne/stats/regression.pyc
in linear_regression(inst, design_matrix, names)
85 logger.info(msg + ', (%s targets, %s regressors)' %
86 (np.product(data.shape[1:]), len(names)))
---> 87 lm_params = _fit_lm(data, design_matrix, names)
88 lm = namedtuple('lm', 'beta stderr t_val p_val mlog10_p_val')
89 lm_fits = {}
/Users/wc47/anaconda/envs/mne-python/lib/python2.7/site-packages/mne/stats/regression.pyc
in _fit_lm(data, design_matrix, names)
125 df = n_rows - n_predictors
126 sqrt_noise_var = np.sqrt(resid_sum_squares /
df).reshape(data.shape[1:])
--> 127 design_invcov = linalg.inv(np.dot(design_matrix.T,
design_matrix))
128 unscaled_stderrs = np.sqrt(np.diag(design_invcov))
129 tiny = np.finfo(np.float64).tiny
/Users/wc47/anaconda/envs/mne-python/lib/python2.7/site-packages/scipy/linalg/basic.pyc
in inv(a, overwrite_a, check_finite)
685 inv_a, info = getri(lu, piv, lwork=lwork, overwrite_lu=1)
686 if info > 0:
--> 687 raise LinAlgError("singular matrix")
688 if info < 0:
689 raise ValueError('illegal value in %d-th argument of
internal '
LinAlgError: singular matrix
---------------------------------------------------------------------------
Thanks in advance!
Best,
Emma
------
Emma(Wei) Chen, Ph.D.
Objects and Knowledge Laboratory
New York University Abu Dhabi
PO Box 129188
Abu Dhabi, United Arab Emirates
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