Add support for diagonal emissions noise in LGSSM models
calebweinreb opened this issue · 0 comments
calebweinreb commented
For LGSSMs with a high-dimensional observation space, inference can be much more efficient by assuming diagonal covariance R
. Specifically, it should be possible to speed up the calculation of Kalman gain and observation log-likelihoods, and also to reduce memory requirements when the noise is dynamic by storing R
as a (ntime x obs_dim) array rather than (ntime x obs_dim x obs_dim).