After fitting the model with g_model.fit(), how can a user extract the parameter estimates?
For example, when I fit a canonical HRF I would like to extract the parameter estimate by which this canonical HRF is weighted for each condition.
Similarly, if I fit a Fourier series with 9 waves, I would expect 9 parameters per condition per individual.
The reason I want to do this is that I am trying to get to a measure of response for each condition and individual. One way of doing this would be to calculate the integral for the timeseries of each condition for each individual. But I would also like to try the more common approach used in neuroimaging of extracting parameter estimates.
Dear Experts,
After fitting the model with g_model.fit(), how can a user extract the parameter estimates?
For example, when I fit a canonical HRF I would like to extract the parameter estimate by which this canonical HRF is weighted for each condition.
Similarly, if I fit a Fourier series with 9 waves, I would expect 9 parameters per condition per individual.
The reason I want to do this is that I am trying to get to a measure of response for each condition and individual. One way of doing this would be to calculate the integral for the timeseries of each condition for each individual. But I would also like to try the more common approach used in neuroimaging of extracting parameter estimates.
Thank you very much!