I want to solve the ill-posed problem y = A x, where
“y” is a known vector (1-d) of data,
“A” is a 2-d matrix with parameters theta.
The functional form of A is known, so you can calculate A as function of the parameters. The vector (1-d) “x” are the unknown values that together with the parameters theta are the ones I want to calculate with the bayesian linear regression.
Thus, the question is how can you write this model in Stan
Extra question: because this is an ill-posed problem, do you have to add an extra term such as the one in Tihkonov regularisation?