EE375 Lecture 15c: Linear Tangent uncertainty propagation
Channel: Michael Dietze
Date: 2020-10-19

Shows how we can use the first two terms of the Taylor Series approximation of a function to estimate the variance in the predictions out of nonlinear model by taking the linear tangent and then applying analytical moments to that linear tangent approximation. Discusses the key role of model sensitivity and input variance in jointly determining output variance. Extends this to a multi-parameter model, showing the need to account for covariances, and then applies this to a simple linear regression model.