Optimizing Methods in Statistics
Proceedings of a Symposium Held at the Center for Tomorrow, the Ohio State University, June 14-16, 1971
Published on 10. May 2014
504 pages
978-1-4832-6034-1 (ISBN)
Description
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 filter learn the system model while the system is operating in real time. By reducing the time necessary for process modeling, the time required to implement the acceptable system design can also be reduced One paper evaluates the parallel structure between duality relationships for the linear functional version of the generalized Neyman-Pearson problem, as well as the duality relationships of linear programming as these apply to bounded-variable linear programming problems. The compendium can prove beneficial to mathematicians, students, and professor of calculus, statistics, or advanced mathematics.
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Content
ContributorsPrefaceThe Efficient Estimation of a Parameter Measurable by Two Instruments of Unknown PrecisionsOptimization Problems in SimulationSome Optimization Problems in Parameter EstimationOptimal Designs and Spline RegressionsIsotonic ApproximationAsymptotically Efficient Estimation of Nonparametric Regression Coefficients (Abstract)Comparisons of Order Statistics and of Spacings from Heterogeneous DistributionsMoment Problems with Convexity Conditions IVariational Methods in Adaptive FilteringNon Linear FilteringA Convergence Theorem for Non Negative Almost Supermartingales and Some ApplicationsOn Relationships Between the Neyman-Pearson Problem and Linear ProgrammingStatistical Control of OptimizationCurrent Capabilities in Mathematical Programming (Abstract)Patterns and Search StatisticsNecessary Conditions for a Local Optimum without Prior Constraint QualificationMathematical Models for Statistical Decision TheoryChance-Constrained Programming: An Extension of Statistical MethodStochastic Allocation of Spare ComponentsOutlier Proneness of Phenomena and of Related DistributionsProblem Areas Requiring Optimizing MethodsStochastic ApproximationAllocation of Observations in Ranking and Selection with Unequal Variances (Abstract)Sequences of Minimal Fractions of 2n Designs of Resolution V (Abstract)Optimum Interval Estimation for the Largest Scale Parameterc-Sample Tests of Homogeneity Against Ordered Alternatives (Abstract)Participants
