Optimizing Methods in Statistics
Proceedings of a Symposium Held at the Center for Tomorrow, the Ohio State University, June 14-16, 1971
- 1st Edition - January 1, 1971
- Imprint: Academic Press
- Editor: Jagdish S. Rustagi
- Language: English
- Paperback ISBN:9 7 8 - 1 - 4 8 3 2 - 4 5 9 5 - 9
- eBook ISBN:9 7 8 - 1 - 4 8 3 2 - 6 0 3 4 - 1
Optimizing Method in Statistics is a compendium of papers dealing with variational methods, regression analysis, mathematical programming, optimum seeking methods, stochastic… Read more
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Request a sales quoteOptimizing 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.
Contributors
Preface
The Efficient Estimation of a Parameter Measurable by Two Instruments of Unknown Precisions
Optimization Problems in Simulation
Some Optimization Problems in Parameter Estimation
Optimal Designs and Spline Regressions
Isotonic Approximation
Asymptotically Efficient Estimation of Nonparametric Regression Coefficients (Abstract)
Comparisons of Order Statistics and of Spacings from Heterogeneous Distributions
Moment Problems with Convexity Conditions I
Variational Methods in Adaptive Filtering
Non Linear Filtering
A Convergence Theorem for Non Negative Almost Supermartingales and Some Applications
On Relationships Between the Neyman-Pearson Problem and Linear Programming
Statistical Control of Optimization
Current Capabilities in Mathematical Programming (Abstract)
Patterns and Search Statistics
Necessary Conditions for a Local Optimum without Prior Constraint Qualification
Mathematical Models for Statistical Decision Theory
Chance-Constrained Programming: An Extension of Statistical Method
Stochastic Allocation of Spare Components
Outlier Proneness of Phenomena and of Related Distributions
Problem Areas Requiring Optimizing Methods
Stochastic Approximation
Allocation 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 Parameter
c-Sample Tests of Homogeneity Against Ordered Alternatives (Abstract)
Participants
- Edition: 1
- Published: January 1, 1971
- No. of pages (eBook): 504
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9781483245959
- eBook ISBN: 9781483260341
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