Piecewise Linear Slope Estimation.

Abstract

This paper presents a method for directly estimating slope values in a noisy piecewise linear function. By imposing a Markov structure on the sequence of slopes, piecewise linear fitting is posed as a maximum a posteriori estimation problem. A dynamic program efficiently solves this by traversing a linearly growing trellis. The alternating maximization algorithm (a kind of pseudo-EM method) is used to estimate the model parameters from data and its convergence behavior is analyzed. Ultrasound shear wave imaging is presented as a primary application. The algorithm is general enough for applicability in other fields, as suggested by an application to the estimation of shifts in financial interest rate data.