I am building a model and i need to multiply a beta \times X but i an not sure how to do it. data { matrix[N, K] y; // observations matrix[N, P] X[K]; // input variables } parameters { matrix[P, K] beta; // X's coefficients } model { // sigma_obs was defined before…

You can use a for loop for (i in 1:N){ y[i, ] ~ multi_normal(mu, Sigma); } where mu is something you should be defined based on i.

Multiply matrix by tensor

carlos_perez December 10, 2020, 3:04pm 4

Thanks.

If i do that i will end defining K independent normal distribution and i need to keep the covariance. is there a another way to define it?

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