Optimum Methods In Statistics PDF Download
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Author | : Ferenc Steiner |
Publisher | : Akademiai Kiads |
Total Pages | : 380 |
Release | : 1997 |
Genre | : Mathematics |
ISBN | : |
Download Optimum Methods in Statistics Book in PDF, ePub and Kindle
Practitioners of different disciplines often have a jungle of erroneous data which unfortunately contain only latently the necessary, immediately usable information. If a suitable model is chosen, the E(i) values calculated by the "best" model parameters are possibly near the primarily given x(i) data which are the raw material of the statistics. The optimum methods of statistics minimize the deviations on the basis of some principle: that of the "least squares" has been generally used for two centuries but statistical procedures based on it work effectively only if the distribution type of the errors is Gaussian or near to it. Since some years, however, global optimums can be economically calculated for whichever functions, consequently the principle of "minimum products" and that of "maximum reciprocals" can also be used both resulting in most frequent value (MFV) procedures which are outlier resistant and their statistical efficiencies have high values in a wide range of error distribution types, i.e., they can extract the information effectively from the primarily given data. The definition and characterization of new norms (besides the old L(2) one) is therefore unavoidable.
Author | : Jagdish S. Rustagi |
Publisher | : Elsevier |
Total Pages | : 376 |
Release | : 2014-05-19 |
Genre | : Mathematics |
ISBN | : 1483295710 |
Download Optimization Techniques in Statistics Book in PDF, ePub and Kindle
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 annealing methods. The text features numerous applications, including: Finding maximum likelihood estimates, Markov decision processes, Programming methods used to optimize monitoring of patients in hospitals, Derivation of the Neyman-Pearson lemma, The search for optimal designs, Simulation of a steel mill. Suitable as both a reference and a text, this book will be of interest to advanced undergraduate or beginning graduate students in statistics, operations research, management and engineering sciences, and related fields. Most of the material can be covered in one semester by students with a basic background in probability and statistics. Covers optimization from traditional methods to recent developments such as Karmarkars algorithm and simulated annealing Develops a wide range of statistical techniques in the unified context of optimization Discusses applications such as optimizing monitoring of patients and simulating steel mill operations Treats numerical methods and applications Includes exercises and references for each chapter Covers topics such as linear, nonlinear, and dynamic programming, variational methods, and stochastic optimization
Author | : Irfan Ali |
Publisher | : CRC Press |
Total Pages | : 434 |
Release | : 2021-11-29 |
Genre | : Business & Economics |
ISBN | : 1000404722 |
Download Optimal Decision Making in Operations Research and Statistics Book in PDF, ePub and Kindle
The book provides insights in the decision-making for implementing strategies in various spheres of real-world issues. It integrates optimal policies in various decisionmaking problems and serves as a reference for researchers and industrial practitioners. Furthermore, the book provides sound knowledge of modelling of real-world problems and solution procedure using the various optimisation and statistical techniques for making optimal decisions. The book is meant for teachers, students, researchers and industrialists who are working in the field of materials science, especially operations research and applied statistics.
Author | : Anthony Atkinson |
Publisher | : OUP Oxford |
Total Pages | : 528 |
Release | : 2007-05-24 |
Genre | : Mathematics |
ISBN | : 0191537942 |
Download Optimum Experimental Designs, With SAS Book in PDF, ePub and Kindle
Experiments on patients, processes or plants all have random error, making statistical methods essential for their efficient design and analysis. This book presents the theory and methods of optimum experimental design, making them available through the use of SAS programs. Little previous statistical knowledge is assumed. The first part of the book stresses the importance of models in the analysis of data and introduces least squares fitting and simple optimum experimental designs. The second part presents a more detailed discussion of the general theory and of a wide variety of experiments. The book stresses the use of SAS to provide hands-on solutions for the construction of designs in both standard and non-standard situations. The mathematical theory of the designs is developed in parallel with their construction in SAS, so providing motivation for the development of the subject. Many chapters cover self-contained topics drawn from science, engineering and pharmaceutical investigations, such as response surface designs, blocking of experiments, designs for mixture experiments and for nonlinear and generalized linear models. Understanding is aided by the provision of "SAS tasks" after most chapters as well as by more traditional exercises and a fully supported website. The authors are leading experts in key fields and this book is ideal for statisticians and scientists in academia, research and the process and pharmaceutical industries.
Author | : Jagdish S. Rustagi |
Publisher | : Academic Press |
Total Pages | : 505 |
Release | : 2014-05-10 |
Genre | : Mathematics |
ISBN | : 1483260348 |
Download Optimizing Methods in Statistics Book in PDF, ePub and Kindle
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.
Author | : Raymond Paul Peterson |
Publisher | : |
Total Pages | : 120 |
Release | : 1950 |
Genre | : Statistics |
ISBN | : |
Download Certain Optimum Statistical Decision Methods Book in PDF, ePub and Kindle
Author | : Ellida M. Khazen |
Publisher | : Xlibris Corporation |
Total Pages | : 320 |
Release | : 2009-11-16 |
Genre | : Education |
ISBN | : 1462807178 |
Download Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations Book in PDF, ePub and Kindle
This book provides the reader with some insight into the mathematical models of random processes with continuous time, stochastic differential equations and stochastic integrals. An advanced development of the mathematical methods of optimal statistical decisions, statistical sequential analysis, and informational estimation of risks, and new methods and solutions to the important problems of the theory of optimal control are presented. The new original results obtained by this author and published shortly in her numerous scientific-research papers are presented in a systematic way in this book. The book is intended for engineers, students, post-graduate students, and scientist researchers. The presentation of the material is accessible to engineers.
Author | : Igor A. Ushakov |
Publisher | : John Wiley & Sons |
Total Pages | : 165 |
Release | : 2013-05-17 |
Genre | : Mathematics |
ISBN | : 1118400704 |
Download Optimal Resource Allocation Book in PDF, ePub and Kindle
A UNIQUE ENGINEERING AND STATISTICAL APPROACH TO OPTIMAL RESOURCE ALLOCATION Optimal Resource Allocation: With Practical Statistical Applications and Theory features the application of probabilistic and statistical methods used in reliability engineering during the different phases of life cycles of technical systems. Bridging the gap between reliability engineering and applied mathematics, the book outlines different approaches to optimal resource allocation and various applications of models and algorithms for solving real-world problems. In addition, the fundamental background on optimization theory and various illustrative numerical examples are provided. The book also features: An overview of various approaches to optimal resource allocation, from classical Lagrange methods to modern algorithms based on ideas of evolution in biology Numerous exercises and case studies from a variety of areas, including communications, transportation, energy transmission, and counterterrorism protection The applied methods of optimization with various methods of optimal redundancy problem solutions as well as the numerical examples and statistical methods needed to solve the problems Practical thoughts, opinions, and judgments on real-world applications of reliability theory and solves practical problems using mathematical models and algorithms Optimal Resource Allocation is a must-have guide for electrical, mechanical, and reliability engineers dealing with engineering design and optimal reliability problems. In addition, the book is excellent for graduate and PhD-level courses in reliability theory and optimization.
Author | : Samuel Kotz |
Publisher | : Springer Science & Business Media |
Total Pages | : 576 |
Release | : 2013-12-01 |
Genre | : Mathematics |
ISBN | : 1461206677 |
Download Breakthroughs in Statistics Book in PDF, ePub and Kindle
Volume III includes more selections of articles that have initiated fundamental changes in statistical methodology. It contains articles published before 1980 that were overlooked in the previous two volumes plus articles from the 1980's - all of them chosen after consulting many of today's leading statisticians.
Author | : John T. Betts |
Publisher | : SIAM |
Total Pages | : 442 |
Release | : 2010-01-01 |
Genre | : Mathematics |
ISBN | : 0898716888 |
Download Practical Methods for Optimal Control and Estimation Using Nonlinear Programming Book in PDF, ePub and Kindle
A focused presentation of how sparse optimization methods can be used to solve optimal control and estimation problems.