This chapter examines the estimation of multivariable linear models
for which the parameters vary in a time-varying manner that depends
in an affine fashion on a known or otherwise measured signal. These
locally linear models which depend on a measurable operating point
are known as linear parameter varying (LPV) models. The
contribution here relative to previous work on the topic is that in
the Gaussian case, an expectation-maximisation (EM) algorithm-based
solution is derived and profiled.