Die Fehlermeldung von W-A selbst ist informativer (zu wenig Normalisierungen, muss mich da noch reinarbeiten), falls Du das noch auf Deine to-do Liste stecken möchtest. Sollte ja kein Problem sein, das einzufangen.
So, jetzt aber wieder an Obamacare :-)
Cheerio,
HM
Warnungen CHS:
/home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/skill_model.py:769: UserWarning: In model baseline with dataset hrs it is not possible to use estimates from the wa estimator as start values for the chs estimator because of the following reasons:
/home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/skill_model.py:868: UserWarning: Fitting model baseline with the wa estimator in order to get start values for the chs estimator failed. Instead naive start params will be used.
/home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/likelihood_function.py:77: RuntimeWarning: overflow encountered in sqrt_linear_update
/home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/likelihood_function.py:77: RuntimeWarning: invalid value encountered in sqrt_linear_update
/home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/fast_routines/kalman_filters.py:290: RuntimeWarning: invalid value encountered in subtract
/home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/likelihood_function.py:64: RuntimeWarning: invalid value encountered in less
janosg
commented
5 years ago
Die Fehlermeldung von W-A selbst ist informativer (zu wenig Normalisierungen, muss mich da noch reinarbeiten), falls Du das noch auf Deine to-do Liste stecken möchtest. Sollte ja kein Problem sein, das einzufangen.
So, jetzt aber wieder an Obamacare :-)
Cheerio, HM
Warnungen CHS:
/home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/skill_model.py:769: UserWarning: In model baseline with dataset hrs it is not possible to use estimates from the wa estimator as start values for the chs estimator because of the following reasons: /home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/skill_model.py:868: UserWarning: Fitting model baseline with the wa estimator in order to get start values for the chs estimator failed. Instead naive start params will be used. /home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/likelihood_function.py:77: RuntimeWarning: overflow encountered in sqrt_linear_update /home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/likelihood_function.py:77: RuntimeWarning: invalid value encountered in sqrt_linear_update /home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/fast_routines/kalman_filters.py:290: RuntimeWarning: invalid value encountered in subtract /home/hmg/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/estimation/likelihood_function.py:64: RuntimeWarning: invalid value encountered in less
Fehler WA:
~/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/model_functions/transition_functions.py in model_coeffs_from_iv_coeffs_linear(iv_coeffs, loading_norminfo, intercept_norminfo, coeff_sum_value, trans_intercept_value) 189 has_trans_intercept=False, loading_norminfo=loading_norminfo, 190 intercept_norminfo=intercept_norminfo, coeff_sum_value=coeff_sum_value, --> 191 trans_intercept_value=trans_intercept_value) 192 193
~/miniconda3/envs/health-cognition/lib/python3.7/site-packages/skillmodels-0.0.33-py3.7.egg/skillmodels/model_functions/transition_functions.py in general_model_coeffs_from_iv_coeffs(iv_coeffs, iv_intercept_position, has_trans_intercept, loading_norminfo, intercept_norminfo, coeff_sum_value, trans_intercept_value) 582 to_check = [coeff_sum_value, loading_norminfo] 583 assert None in to_check, ('Overidentified scale') --> 584 assert to_check != [None, None], ('Underidentified scale') 585 586 to_check = [trans_intercept_value, intercept_norminfo]
AssertionError: Underidentified scale