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Optimization Techniques in Statistics
Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimization in function spaces are also discussed, as are stochastic optimization in simulation, including ...
Sikri to Sunnyvale
Autobiography of an Indian statistician who lives in California, USA.
Bayesian Analysis and Uncertainty in Economic Theory
No descriptive material is available for this title.
Teaching of Statistics and Statistical Consulting
Teaching of Statistics and Statistical Consulting is a collection of papers dealing with graduate programs in statistics; teaching service courses and short courses; and training statisticians for employment in industry and government. Some papers also deal with the role of statistical consulting in graduate training and teaching statistics at the Open University. One paper describes some observations made on graduate program in statistics, citing concerns of professionalism, competency, and a highly structured university curriculum. Another paper takes a task analysis approach to designing a regression analysis course where, with proper course structuring, students will actively learn to do...
Recent Advances in Statistics
Recent Advances in Statistics: Papers in Honor of Herman Chernoff on His Sixtieth Birthday is a collection of papers on statistics in honor of Herman Chernoff on the occasion of his 60th birthday. Topics covered range from sequential analysis (including designs) to optimization (including control theory), nonparametrics (including large sample theory), and statistical graphics. Comprised of 27 chapters, this book begins with a discussion on optimal stopping of Brownian motion, followed by an analysis of sequential design of comparative clinical trials. A two-sample sequential test for shift with one sample size fixed in advance is then presented. Subsequent chapters focus on set-valued param...
Distributional Reinforcement Learning
The first comprehensive guide to distributional reinforcement learning, providing a new mathematical formalism for thinking about decisions from a probabilistic perspective. Distributional reinforcement learning is a new mathematical formalism for thinking about decisions. Going beyond the common approach to reinforcement learning and expected values, it focuses on the total reward or return obtained as a consequence of an agent's choices—specifically, how this return behaves from a probabilistic perspective. In this first comprehensive guide to distributional reinforcement learning, Marc G. Bellemare, Will Dabney, and Mark Rowland, who spearheaded development of the field, present its key...
Patents and Cartographic Inventions
This book explores the US patent system, which helped practical minded innovators establish intellectual property rights and fulfill the need for achievement that motivates inventors and scholars alike. In this sense, the patent system was a parallel literature: a vetting institution similar to the conventional academic-scientific-technical journal insofar as the patent examiner was both editor and peer reviewer, while the patent attorney was a co-author or ghost writer. In probing evolving notions of novelty, non-obviousness, and cumulative innovation, Mark Monmonier examines rural address guides, folding schemes, world map projections, diverse improvements of the terrestrial globe, mechanical route-following machines that anticipated the GPS navigator, and the early electrical you-are-here mall map, which opened the way for digital cartography and provided fodder for patent trolls, who treat the patent largely as a license to litigate.
Nonparametric Econometric Methods and Application
The present Special Issue collects a number of new contributions both at the theoretical level and in terms of applications in the areas of nonparametric and semiparametric econometric methods. In particular, this collection of papers that cover areas such as developments in local smoothing techniques, splines, series estimators, and wavelets will add to the existing rich literature on these subjects and enhance our ability to use data to test economic hypotheses in a variety of fields, such as financial economics, microeconomics, macroeconomics, labor economics, and economic growth, to name a few.
Extremal Methods and Systems Analysis
The papers appearing in this Volume were selected from a collec tion of papers presented at the Internationa~ Symposium on Extrema~ Methods and Systems Ana~ysis on the Occasion of Professor A. Charnes' 60th Birthday, at the University of Texas in Austin, 13-15 September 1977. As coeditors, we have followed the normal editorial procedures of scholarly journals. We have obtained invaluable assistance from a number of colleagues who essentially performed the duties of associate editors, coordinating most of the reviews. All papers except those appearing in the Historica~ Perspectives section were refereed by at least two individuals with competency in the respective area. Because of the wide ra...
