The TestZeroInflatedModel_probit issue appears to be a failure to
converge: as it does trigger warnings of that, and it's already skipped
on i386, I intend to ignore it.
qemu-arm64:
>>> a
object at 0x4000d31130>
>>> a.res1.params
Traceback (most recent call last):
File "", line 1, in
AttributeError: 'TestZeroInflatedModel_probit' object has no attribute
'res1'
>>> a.setup_class()
/usr/lib/python3/dist-packages/statsmodels/base/model.py:567:
ConvergenceWarning: Maximum Likelihood optimization failed to converge.
Check mle_retvals
warn("Maximum Likelihood optimization failed to converge. "
>>> a.res1.params
array([ 0.06225336, -0.64293239, -0.08217881, 0.00856726, -0.02679518,
1.4823691 ])
>>>
alpha=np.ones(6);alpha[-2:]=0;res_reg=a.res1.model.fit_regularized(alpha=alpha*0.01,disp=0,maxiter=500)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:71:
ConvergenceWarning: QC check did not pass for 4 out of 4 parameters
Try increasing solver accuracy or number of iterations, decreasing
alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:144:
ConvergenceWarning: Could not trim params automatically due to failed QC
check. Trimming using trim_mode == 'size' will still work.
warnings.warn(msg, ConvergenceWarning)
>>> res_reg.params
array([ 0., 0., 0., 0., -0.02679517,
1.48236838])
>>>
alpha=np.ones(6);alpha[-2:]=0;res_reg=a.res1.model.fit_regularized(alpha=alpha*0.0,disp=0,maxiter=500)
>>> res_reg.params
array([ 0.0622522 , -0.6429312 , -0.08217381, 0.00856762, -0.02679573,
1.48237116])
>>>
alpha=np.ones(6);alpha[-2:]=0;res_reg=a.res1.model.fit_regularized(alpha=alpha*1e-6,disp=0,maxiter=500)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:71:
ConvergenceWarning: QC check did not pass for 4 out of 4 parameters
Try increasing solver accuracy or number of iterations, decreasing
alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:144:
ConvergenceWarning: Could not trim params automatically due to failed QC
check. Trimming using trim_mode == 'size' will still work.
warnings.warn(msg, ConvergenceWarning)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:71:
ConvergenceWarning: QC check did not pass for 4 out of 6 parameters
Try increasing solver accuracy or number of iterations, decreasing
alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:144:
ConvergenceWarning: Could not trim params automatically due to failed QC
check. Trimming using trim_mode == 'size' will still work.
warnings.warn(msg, ConvergenceWarning)
>>> res_reg.params
array([ 0.06225361, -0.64293282, -0.08218008, 0.0085677 , -0.02679533,
1.48236748])
>>>
alpha=np.ones(6);alpha[-2:]=0;res_reg=a.res1.model.fit_regularized(alpha=alpha*1,disp=0,maxiter=500)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:71:
ConvergenceWarning: QC check did not pass for 2 out of 4 parameters
Try increasing solver accuracy or number of iterations, decreasing
alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:144:
ConvergenceWarning: Could not trim params automatically due to failed QC
check. Trimming using trim_mode == 'size' will still work.
warnings.warn(msg, ConvergenceWarning)
>>> res_reg.params
array([ 0., -0.64270273, -0.08204933, 0., -0.02679321,
1.48237335])
>>>
alpha=np.ones(6);alpha[-2:]=0;res_reg=a.res1.model.fit_regularized(alpha=alpha*100,disp=0,maxiter=500)
>>> res_reg.params
array([ 0.05531257, -0.62025715, -0.06936752, 0.00781262, -0.02661252,
1.48282813])
>>>
alpha=np.ones(6);alpha[-2:]=0;res_reg=a.res1.model.fit_regularized(alpha=alpha*1e-4,disp=0,maxiter=500)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:71:
ConvergenceWarning: QC check did not pass for 4 out of 4 parameters
Try increasing solver accuracy or number of iterations, decreasing
alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:144:
ConvergenceWarning: Could not trim params automatically due to failed QC
check. Trimming using trim_mode == 'size' will still work.
warnings.warn(msg, ConvergenceWarning)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:71:
ConvergenceWarning: QC check did not pass for 4 out of 6 parameters
Try increasing solver accuracy or number of iterations, decreasing
alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
/usr/lib/python3/dist-packages/statsmodels/base/l1_solvers_common.py:144:
ConvergenceWarning: Could not trim params
