Optimizing Methods in Statistics
eBook - PDF

Optimizing Methods in Statistics

Proceedings of a Symposium Held at the Center for Tomorrow, the Ohio State University, June 14-16, 1971

  1. 504 pages
  2. English
  3. PDF
  4. Only available on web
eBook - PDF

Optimizing Methods in Statistics

Proceedings of a Symposium Held at the Center for Tomorrow, the Ohio State University, June 14-16, 1971

Book details
Table of contents
Citations

About This Book

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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Information

Publisher
Academic Press
Year
2014
ISBN
9781483260341
Topic
Mathematik
Subtopic
Angewandte Mathematik

Table of contents

  1. Front Cover
  2. Optimizing Methods in Statistics
  3. Copyright Page
  4. Table of Contents
  5. CONTRIBUTORS
  6. PREFACE
  7. CHAPTER 1. THE EFFICIENT ESTIMATION OF A PARAMETER MEASURABLE BY TWO INSTRUMENTS OF UNKNOWN PRECISIONS
  8. CHAPTER 2. OPTIMIZATION PROBLEMS IN SIMULATION
  9. CHAPTER 3. SOME OPTIMIZATION PROBLEMS IN PARAMETER ESTIMATION
  10. CHAPTER 4. OPTIMAL DESIGNS AND SPLINE REGRESSION
  11. CHAPTER 5. ISOTONIC APPROXIMATION
  12. CHAPTER 6. ASYMPTOTICALLY EFFICIENT ESTIMATION OF NONPARAMETRIC REGRESSION COEFFICIENTS
  13. CHAPTER 7. COMPARISONS OF ORDER STATISTICS AND OF SPACINGS FROM HETEROGENEOUS DISTRIBUTIONS
  14. CHAPTER 8. MOMENT PROBLEMS WITH CONVEXITY CONDITIONS
  15. CHAPTER 9. VARIATIONAL METHODS IN ADAPTIVE FILTERING
  16. CHAPTER 10. NON LINEAR FILTERING
  17. CHAPTER 11. A CONVERGENCE THEOREM FOR NON NEGATIVE ALMOST SUPERMARTINGALES AND SOME APPLICATIONS
  18. CHAPTER 12. ON RELATIONSHIPS BETWEEN THE NEYMAN-PEARSON PROBLEM AND LINEAR PROGRAMMING
  19. CHAPTER 13. STATISTICAL CONTROL OF OPTIMIZATION
  20. CHAPTER 14. CURRENT CAPABILITIES IN MATHEMATICAL PROGRAMMING
  21. CHAPTER 15. PATTERNS AND SEARCH STATISTICS
  22. CHAPTER 16. NECESSARY CONDITIONS FOR A LOCAL OPTIMUM WITHOUT PRIOR CONSTRAINT QUALIFICATION
  23. CHAPTER 17. MATHEMATICAL MODELS FOR STATISTICAL DECISION THEORY1
  24. CHAPTER 18. CHANCE-CONSTRAINED PROGRAMMING:AN EXTENSION OF STATISTICAL METHOD
  25. CHAPTER 19. STOCHASTIC ALLOCATION OF SPARE COMPONENTS
  26. CHAPTER 20. OUTLIER PRONENESS OF PHENOMENA AND OF RELATED DISTRIBUTIONS
  27. CHAPTER 21. PROBLEM AREAS REQUIRING OPTIMIZING METHODS
  28. CHAPTER 22. STOCHASTIC APPROXIMATION
  29. CHAPTER 23. ALLOCATION OF OBSERVATIONS IN RANKING AND SELECTION WITH UNEQUAL VARIANCES
  30. CHAPTER 24. SEQUENCES OF MINIMAL FRACTIONS OF2n DESIGNS OF RESOLUTION V
  31. CHAPTER 25. OPTIMUM INTERVAL ESTIMATION FOR THE LARGEST SCALE PARAMETER
  32. CHAPTER 26. c-SAMPLE TESTS OF HOMOGENEITY AGAINST ORDERED ALTERNATIVES
  33. PARTICIPANTS