Description: Good; Hardcover; Withdrawn library copy with the standard library markings; Moderate wear to the covers; Library stamps to the endpapers; Text pages are clean & unmarked; Good binding with a straight spine; This book will be stored and delivered in a sturdy cardboard box with foam padding; Medium Format (8.5" – 9.75" tall); Yellow covers with title in red lettering; 1982, Springer-Verlag Publishing; 201 pages; "Markov Random Fields (Applications of Mathematics)," by Y.A. Rozanov. Seller Background: We are a small, online bookseller based out of Bellingham, WA specializing in modern rare and out-of-print titles. We have been active in the book trade for over ten years and have been an active Ebay member since 2002. All of our books are carefully cleaned and restored to the best possible condition prior to being offered for sale. Our books are graded conservatively with ex-library books never graded above "Good" and used books very rarely graded above "Very Good". Domestic Shipping Notes: We use a fulfillment company (Amazon Fulfillment) to package and ship all orders shipping to a location within the USA. Orders placed with "Standard Shipping" ship by USPS Media Mail. Orders placed with "Expedited Shipping" ship by either Fed-Ex or UPS 2-day delivery. A street address is required for the Expedited Shipping service (FedEx/UPS cannot delivery to PO Boxes). Our fulfillment company also offers a 1-day/overnight shipping option which is available upon special request. Return Policy: We accept returns for any reason as long as we are notified of your intent to return within two weeks of the date of receipt. The buyer is responsible for return shipping on all discretionary returns. If the return is due to an error in our description or from damage caused by the shipping carrier we will reimburse all shipping costs paid by the buyer. Book Info: In this book we study Markov random functions of several variables. What is traditionally meant by the Markov property for a random process (a random function of one time variable) is connected to the concept of the phase state of the process and refers to the independence of the behavior of the process in the future from its behavior in the past, given knowledge of its state at the present moment. Extension to a generalized random process immediately raises nontrivial questions about the definition of a suitable" phase state," so that given the state, future behavior does not depend on past behavior. Attempts to translate the Markov property to random functions of multi-dimensional "time," where the role of "past" and "future" are taken by arbitrary complementary regions in an appro priate multi-dimensional time domain have, until comparatively recently, been carried out only in the framework of isolated examples. How the Markov property should be formulated for generalized random functions of several variables is the principal question in this book. We think that it has been substantially answered by recent results establishing the Markov property for a whole collection of different classes of random functions. These results are interesting for their applications as well as for the theory. In establishing them, we found it useful to introduce a general probability model which we have called a random field. In this book we investigate random fields on continuous time domains. Contents CHAPTER 1 General Facts About Probability Distributions 1. Inventory #: SKU-U06CI15801046
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