Model Definition #
In this library, linear regression models take the following form:
\[\mathbf{y}_t = \mathbf{C} \mathbf{x}_{t} + \mathbf{d}\] \[\mathbf{z}_t \sim \mathcal{N}\left(\mathbf{y}_t , \mathbf{R} \right)\]where \( \mathbf{x}_{t} \) , \( \mathbf{y}_{t} \) , and \( \mathbf{z}_{t} \) the input, output, and measurement, respectively; \( \mathbf{C} \) is the output matrix; \( \mathbf{d} \) is the output bias; and \( \mathbf{R} \) is the covariance of the assumed Gaussian measurement noise.