The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.
Chapter 8 presents some new robustness results, which deal with inference in two population problems. This book will prove useful to advance graduate mathematical statistics students.
For researchers, this book provides a thorough literature review that summarizes latest progress in the area, which can be a good reference for conducting future research.
Alessandro Giuliani Abstract Considering biological systems at different levels of organization as complex networks in which nodes (genes, proteins, metabolites...) are each other connected by (co-expression, physical interactions) is a ...
By comparing the solution of the kth best scenario with the kth best optimal solution, the scenarios are made ... g) – f'(#") < z Vie [N] g(x) < 0 x e o st e o (%) To give a concrete example we use again the assignment problem. min z ...
the existence of multiple proofs of theorems serves an overarching purpose that is often overlooked, one that is analogous to the role of confirmation in the natural sciences. For just as agreement among the results of different ...
Robustness and Evolvability in Living Systems tackles this perplexing paradox. The book explores why genetic changes do not cause organisms to fail catastrophically and how evolution shapes organisms' robustness.
Comprised of 14 chapters, this book begins with an introduction to robust estimation, paying particular attention to iteration schemes and error structure of estimators.
This volume collects most of the papers presented at the International Workshop on Robustness in Identification and Control, held in Torino (Italy) in 1988.
The series is devoted to the publication of high-level monographs and surveys which cover the whole spectrum of probability and statistics. The books of the series are addressed to both experts and advanced students.
New Tools for Robustness of Linear Systems