This is a preview. Log in through your library . Abstract In some applications linear approximations to non-linear models are desirable. They bring the benefits of computational simplicity and access ...

Lecture Notes-Monograph Series, Vol. 49, Optimality: The Second Erich L. Lehmann Symposium (2006), pp. 291-311 (21 pages) We analyze the (unconditional) distribution of a linear predictor that is ...

1.) Harald Uhlig's toolkit of MATLAB programs. Run the readme.m file to see what's there. - Toolkit_4.1.zip 2.) The program bigshow.m takes AR and MA coefficients as input, and then plots a simulated ...

Sometimes, it’s easy for a computer to predict the future. Simple phenomena, such as how sap flows down a tree trunk, are straightforward and can be captured in a few lines of code using what ...

This course studies approximation algorithms – algorithms that are used for solving hard optimization problems. Such algorithms find approximate (slightly suboptimal) solutions to optimization ...