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Abstrak :
A discussion of some topics in the theory of large deviations such as moment-generating functions and Chernoff's theorem, and of aspects of estimation and testing in large samples, such as exact slopes of test statistics.

Abstrak :
Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in robustness has been added and the reference list has been expanded and updated from the 1977 edition.

Abstrak :
Provides a comprehensive theory of the approximations of quantile processes in light of recent advances, as well as some of their statistical applications.

Abstrak :
Recent advances in system reliability discusses developments in modern reliability theory such as signatures, multi-state systems and statistical inference. It describes the latest achievements in these fields, and covers the application of these achievements to reliability engineering practice. The chapters cover a wide range of new theoretical subjects and have been written by leading experts in reliability theory and its applications. The topics include, concepts and different definitions of signatures (D-spectra), their properties and applications to reliability of coherent systems and network-type structures, Lz-transform of Markov stochastic process and its application to multi-state system reliability analysis, methods for cost-reliability and cost-availability analysis of multi-state systems, optimal replacement and protection strategy, and statistical inference. Recent advances in system reliability presents many examples to illustrate the theoretical results. Real world multi-state systems, such as power generation and transmission, refrigeration, and production systems, are considered in the form of case studies.

Abstrak :
The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents, a clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis, probabilistic models for random variables and functions needed to formulate stochastic equations describing realistic problems in engineering and applied sciences, practical methods for quantifying the uncertain parameters in the definition of stochastic equations, solving approximately these equations, and assessing the accuracy of approximate solutions.

Abstrak :
This book will expose the reader to some of the fundamental methodology in non-cooperative game theory, and highlight some numerical methods, along with some relevant applications. Since the early development days, differential game theory has had a significant impact in such diverse disciplines as applied mathematics, economics, systems theory, engineering, operations, research, biology, ecology, environmental sciences, among others. Modern game theory now relies on wide ranging mathematical and computational methods, and relevant applications that are rich and challenging. Game theory has been widely recognized as an important tool in many fields. Importance of game theory to economics is illustrated by the fact that numerous game theorists, such as John Forbes Nash, Jr., Robert J. Aumann and Thomas C. Schelling, have won the Nobel Memorial Prize in Economics Sciences. Simply put, game-theory has the potential to reshape the analysis of human interaction.

Abstrak :
This monograph and translation from the Russian describes in detail and comments on the fundamentals of metrology. The basic concepts of metrology, the principles of the International System of Units SI, the theory of measurement uncertainty, the new methodology of estimation of measurement accuracy on the basis of the uncertainty concept, as well as the methods for processing measurement results and estimating their uncertainty are discussed from the modern position. It is shown that the uncertainty concept is compatible with the classical theory of accuracy. The theory of random uncertainties is supplemented with their most general description on the basis of generalized normal distribution; the instrumental systematic errors are presented in connection with the methodology of normalization of the metrological characteristics of measuring instruments. The information about modern systems of traceability is given. All discussed theoretical principles and calculation methods are illustrated with examples.