You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I think that in each part (1,2,3) of this exercise the conditional component is not considered.
For example in the first, you considered p(x(t+1)) = p(x(t+1) | y1, ... , yt), but the knowledge of y1, ... , yt influences the density of x(t+1) since x(t+1) depends on y(t) (y(t) influences x(t) which in turn influences x(t+1)) and so on...
I think that you should use the formula of conditional Gaussian to compute p(x(t+1) | y1, ... , yt) since both x(t+1) and y1, ... , yt are Gaussian multivariate densities.
The text was updated successfully, but these errors were encountered:
I think that in each part (1,2,3) of this exercise the conditional component is not considered.
For example in the first, you considered p(x(t+1)) = p(x(t+1) | y1, ... , yt), but the knowledge of y1, ... , yt influences the density of x(t+1) since x(t+1) depends on y(t) (y(t) influences x(t) which in turn influences x(t+1)) and so on...
I think that you should use the formula of conditional Gaussian to compute p(x(t+1) | y1, ... , yt) since both x(t+1) and y1, ... , yt are Gaussian multivariate densities.
The text was updated successfully, but these errors were encountered: