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This book presents recent methods of study on the asymptotic behavior of solutions of abstract differential equations such as stability, exponential dichotomy, periodicity, almost periodicity, and almost automorphy of solutions. The chosen methods are described in a way that is suitable to those who have some experience with ordinary differential equations. The book is intended for graduate students and researchers in the related areas.

Differential equations --- Asymptotic distribution (Probability theory) --- Asymptotic expansions --- Central limit theorem --- Distribution (Probability theory) --- 517.91 Differential equations --- Asymptotic theory.

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White noise analysis is an advanced stochastic calculus that has developed extensively since three decades ago. It has two main characteristics. One is the notion of generalized white noise functionals, the introduction of which is oriented by the line of advanced analysis, and they have made much contribution to the fields in science enormously. The other characteristic is that the white noise analysis has an aspect of infinite dimensional harmonic analysis arising from the infinite dimensional rotation group. With the help of this rotation group, the white noise analysis has explored new are

White noise theory. --- Gaussian processes. --- Distribution (Probability theory) --- Stochastic processes --- White noise analysis --- Stochastic analysis

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Chance continues to govern our lives in the 21st Century. From the genes we inherit and the environment into which we are born, to the lottery ticket we buy at the local store, much of life is a gamble. In business, education, travel, health, and marriage, we take chances in the hope of obtaining something better. Chance colors our lives with uncertainty, and so it is important to examine it and try to understand about how it operates in a number of different circumstances. Such understanding becomes simpler if we take some time to learn a little about probability, since probability is the natural language of uncertainty. This second edition of Chance Rules again recounts the story of chance through history and the various ways it impacts on our lives. Here you can read about the earliest gamblers who thought that the fall of the dice was controlled by the gods, as well as the modern geneticist and quantum theory researcher trying to integrate aspects of probability into their chosen speciality. Example included in the first addition such as the infamous Monty Hall problem, tossing coins, coincidences, horse racing, birthdays and babies remain, often with an expanded discussion, in this edition. Additional material in the second edition includes, a probabilistic explanation of why things were better when you were younger, consideration of whether you can use probability to prove the existence of God, how long you may have to wait to win the lottery, some court room dramas, predicting the future, and how evolution scores over creationism. Chance Rules lets you learn about probability without complex mathematics. Brian Everitt is Professor Emeritus at King's College, London. He is the author of over 50 books on statistics. .

Statistics. --- Probability Theory and Stochastic Processes. --- Statistics, general. --- Distribution (Probability theory). --- Statistique --- Distribution (Théorie des probabilités) --- Chance --- Probabilities --- Chance. --- Probabilities. --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Probability --- Statistical inference --- Mathematics. --- Combinations --- Least squares --- Mathematical statistics --- Risk --- Fortune --- Necessity (Philosophy) --- Distribution (Probability theory. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Distribution functions --- Frequency distribution --- Characteristic functions --- Statistics .

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Genetics --- Génétique --- Statistical methods --- Méthodes statistiques --- Biology --- Distribution (Probability theory) --- Epidemiology --- Mathematical statistics --- Oncology --- Statistics --- Statistics as Topic --- Cocarcinogenesis --- Genetics, Population --- Mathematics --- Génétique --- Méthodes statistiques --- EPUB-LIV-FT LIVSTATI SPRINGER-B --- Biology - Mathematics --- Genetics - Mathematics

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To assess the past achievement and to provide a road map for future research, an IMA participating institution conference entitled "Conference on Asymptotic Analysis in Stochastic Processes, Nonparametric Estimation, and Related Problems" was held at Wayne State University, September 15-17, 2006. This conference was also held to honor Professor Rafail Z. Khasminskii for his fundamental contributions to many aspects of stochastic processes and nonparametric estimation theory on the occasion of his seventy-fifth birthday. It assembled an impressive list of invited speakers, who are renowned leaders in the fields of probability theory, stochastic processes, stochastic differential equations, as well as in the nonparametric estimation theory, and related fields. A number of invited speakers were early developers of the fields of probability and stochastic processes, establishing the foundation of the Modern probability theory. After the conference, to commemorate this special event, an IMA volume dedicated to Professor Rafail Z. Khasminskii was put together. It consists of nine papers on various topics in probability and statistics. They include authoritative expositions as well as significant research papers of current interest. It is conceivable that the volume will have a lasting impact on the further development of stochastic analysis and nonparametric estimation.

Mathematics. --- Probability Theory and Stochastic Processes. --- Applications of Mathematics. --- Distribution (Probability theory). --- Mathématiques --- Distribution (Théorie des probabilités) --- Nonparametric statistics. --- Stochastic analysis. --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Stochastic analysis --- Nonparametric statistics --- Distribution-free statistics --- Statistics, Distribution-free --- Statistics, Nonparametric --- Analysis, Stochastic --- Applied mathematics. --- Engineering mathematics. --- Probabilities. --- Mathematical statistics --- Mathematical analysis --- Stochastic processes --- Distribution (Probability theory. --- Math --- Science --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Engineering --- Engineering analysis --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Risk