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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 ...
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...
Optimizing Methods in Statistics
Optimizing Method in Statistics is a compendium of papers dealing with variational methods, regression analysis, mathematical programming, optimum seeking methods, stochastic control, optimum design of experiments, optimum spacings, and order statistics. One paper reviews three optimization problems encountered in parameter estimation, namely, 1) iterative procedures for maximum likelihood estimation, based on complete or censored samples, of the parameters of various populations; 2) optimum spacings of quantiles for linear estimation; and 3) optimum choice of order statistics for linear estimation. Another paper notes the possibility of posing various adaptive filter algorithms to make the ...
Variational Methods in Statistics
Variational Methods in Statistics
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...
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.
