Update guessing and slipping parameters from full conditional distribution.
update_sg(Y, Q, ALPHAS, ss_old, as0, bs0, ag0, bg0)
A N by J matrix
of observed responses.
A N by K matrix
indicating which skills are required for which items.
A N by K matrix
of latent attributes.
A J vector
of item slipping parameters from prior iteration.
Slipping prior alpha parameter for Beta distribution.
Slipping prior beta parameter for Beta distribution.
Guessing prior alpha parameter for Beta distribution.
Guessing prior beta parameter for Beta distribution.
A list with two J vectors
of guessing and slipping parameters.