A python implementation of the algorithm used to generate optimal piecewise linear approximations of convex functions proposed by Imamoto and Tang [1]. The algorithm uses an iterative search to find ...

In this project, we provide a method to construct piecewise local linear approximations of a black box model. The main idea behind building piecewise approximations is to divide the feature space into ...

The circumference of a sphere is measured to be 24 cm, with a possible error of 0.25 cm. Use the differential \(dV\) to estimate the maximum error in the calculated ...

Abstract: This chapter provides a definition of linear process and distinguishes between linear approximation and linear representation of nonlinear models. It briefly gives some examples that better ...

Abstract: We consider the problem of online sparse linear approximation, where a learner sequentially predicts the best sparse linear approximations of an as yet unobserved sequence of measurements in ...

We consider a general class of nonlinear optimal policy problems involving forward-looking constraints (such as the Euler equations that are typically present as structural equations in DSGE models), ...