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An Introduction to Continuous-Time Stochastic Processes
This textbook, now in its fourth edition, offers a rigorous and self-contained introduction to the theory of continuous-time stochastic processes, stochastic integrals, and stochastic differential equations. Expertly balancing theory and applications, it features concrete examples of modeling real-world problems from biology, medicine, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required. Unlike other books on stochastic methods that specialize in a specific field of applications, this volume examines the ways in which similar stochastic methods can be applied across different fields. Beginning with the fundamentals of probability, the au...
Bayesian Nonparametrics
This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian non-parametrics.
Asymptotics in Statistics
This is the second edition of a coherent introduction to the subject of asymptotic statistics as it has developed over the past 50 years. It differs from the first edition in that it is now more 'reader friendly' and also includes a new chapter on Gaussian and Poisson experiments, reflecting their growing role in the field. Most of the subsequent chapters have been entirely rewritten and the nonparametrics of Chapter 7 have been amplified. The volume is not intended to replace monographs on specialized subjects, but will help to place them in a coherent perspective. It thus represents a link between traditional material - such as maximum likelihood, and Wald's Theory of Statistical Decision Functions -- together with comparison and distances for experiments. Much of the material has been taught in a second year graduate course at Berkeley for 30 years.
Academic Genealogy of Mathematicians
Burn for Burn
Asymptotic Methods in Statistical Decision Theory
This book grew out of lectures delivered at the University of California, Berkeley, over many years. The subject is a part of asymptotics in statistics, organized around a few central ideas. The presentation proceeds from the general to the particular since this seemed the best way to emphasize the basic concepts. The reader is expected to have been exposed to statistical thinking and methodology, as expounded for instance in the book by H. Cramer [1946] or the more recent text by P. Bickel and K. Doksum [1977]. Another pos sibility, closer to the present in spirit, is Ferguson [1967]. Otherwise the reader is expected to possess some mathematical maturity, but not really a great deal of deta...
Melviano
Benci jadi cinta? Itu adalah segelintir kalimat yang tak asing didengar. Tapi berbeda dengan kisah seorang gadis bernama Grace Lakhaesa yang baru saja masuk ke SMA. Akibat kesalahan yang dilakukan pada kakak kelasnya, membuatnya harus masuk ke kehidupan cowok bernama Melviano Afkar Wesley, yang notabennya adalah most popurel dan most wanted di SMA Marga Satya ini. Konflik antara persahabatan, keluarga, kehancuran sebuah gengster, dan juga pengkhianatan akan tercipta dalam satu kisah cerita ini. Ketika keduanya sudah terikat oleh sebuah hubungan dan hati, berbagai macam masalah dan ancaman menghampiri keduanya. Akankah Grace siap memilih antara keluarga, sahabat atau cinta? Atau bahkan pasrah berakhir menyedihkan dan terhanyut dalam kesedihan? Inilah kisah asmara anak remaja yang terangkum dalam cerita MELVIANO.
Random Integral Equations with Applications to Life Sciences and Engineering
In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator ...
The Recluse of Loyang
"Few thinkers have stood as squarely at both the center and the periphery of an intellectual movement as has Shao Yung (1011-1077). Ethical model and eccentric, socialite and eremite, Shao Yung is perhaps not only the greatest enigma of early Neo-Confucianism, but also one of its undisputed giants. In this impressive life-and-thought study, Don J. Wyatt painstakingly sifts through all available evidence relating to Shao Yung and his scholarship to provide a portrait that fully exposes the moral center of the man and his work. Drawing on the abundant store of letters and accounts by Shao's contemporaries and his own much-neglected poetry, Wyatt has assembled a study that intimately relates Sh...
Topics in the Foundation of Statistics
Foundational research focuses on the theory, but theories are to be related also to other theories, experiments, facts in their domains, data, and to their uses in applications, whether of prediction, control, or explanation. A theory is to be identified through its class of models, but not so narrowly as to disallow these roles. The language of science is to be studied separately, with special reference to the relations listed above, and to the consequent need for resources other than for theoretical description. Peculiar to the foundational level are questions of completeness (specifically in the representation of measurement), and of interpretation (a topic beset with confusions of truth and evidence, and with inappropriate metalinguistic abstraction).
