The Generic Chaining: Upper and Lower Bounds of Stochastic Processes
暫譯: 通用鏈接:隨機過程的上界與下界
Talagrand, Michel
- 出版商: Springer
- 出版日期: 2010-10-21
- 售價: $4,390
- 貴賓價: 9.5 折 $4,171
- 語言: 英文
- 頁數: 222
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3642063861
- ISBN-13: 9783642063862
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相關分類:
機率統計學 Probability-and-statistics
海外代購書籍(需單獨結帳)
相關主題
商品描述
Author's Note:
The material of this book has been reworked and expanded with a lot more detail and published in the author's 2014 book "Upper and Lower Bounds for Stochastic Processes" (Ergebnisse Vol. 60, ISBN 978-3-642-54074-5). That book is much easier to read and covers everything that is in "The Generic Chaining" book in a more detailed and comprehensible way.
************What is the maximum level a certain river is likely to reach over the next 25 years? (Having experienced three times a few feet of water in my house, I feel a keen personal interest in this question. ) There are many questions of the same nature: what is the likely magnitude of the strongest earthquake to occur during the life of a planned building, or the speed of the strongest wind a suspension bridge will have to stand? All these situations can be modeled in the same manner. The value X of the quantity of interest (be it water t level or speed of wind) at time t is a random variable. What can be said about the maximum value of X over a certain range of t? t A collection of random variables (X ), where t belongs to a certain index t set T, is called a stochastic process, and the topic of this book is the study of the supremum of certain stochastic processes, and more precisely to ?nd upper and lower bounds for the quantity EsupX . (0. 1) t t?T Since T might be uncountable, some care has to be taken to de?ne this quantity. For any reasonable de?nition of Esup X we have t t?T EsupX =sup{EsupX; F?T, F ?nite}, (0. 2) t t t?T t?F an equality that we will take as the de?nition of the quantity Esup X . t t?T Thus, the crucial case for the estimation of the quantity (0.
The material of this book has been reworked and expanded with a lot more detail and published in the author's 2014 book "Upper and Lower Bounds for Stochastic Processes" (Ergebnisse Vol. 60, ISBN 978-3-642-54074-5). That book is much easier to read and covers everything that is in "The Generic Chaining" book in a more detailed and comprehensible way.
************What is the maximum level a certain river is likely to reach over the next 25 years? (Having experienced three times a few feet of water in my house, I feel a keen personal interest in this question. ) There are many questions of the same nature: what is the likely magnitude of the strongest earthquake to occur during the life of a planned building, or the speed of the strongest wind a suspension bridge will have to stand? All these situations can be modeled in the same manner. The value X of the quantity of interest (be it water t level or speed of wind) at time t is a random variable. What can be said about the maximum value of X over a certain range of t? t A collection of random variables (X ), where t belongs to a certain index t set T, is called a stochastic process, and the topic of this book is the study of the supremum of certain stochastic processes, and more precisely to ?nd upper and lower bounds for the quantity EsupX . (0. 1) t t?T Since T might be uncountable, some care has to be taken to de?ne this quantity. For any reasonable de?nition of Esup X we have t t?T EsupX =sup{EsupX; F?T, F ?nite}, (0. 2) t t t?T t?F an equality that we will take as the de?nition of the quantity Esup X . t t?T Thus, the crucial case for the estimation of the quantity (0.
商品描述(中文翻譯)
作者註解:本書的內容經過重新整理和擴充,並在作者2014年的著作《隨機過程的上界和下界》(Ergebnisse 第60卷,ISBN 978-3-642-54074-5)中發表。該書的可讀性更高,並以更詳細和易於理解的方式涵蓋了《通用鏈接》一書中的所有內容。
************某條河流在接下來25年內可能達到的最大水位是多少?(因為我曾經三次在家中經歷幾英尺的水,我對這個問題有著強烈的個人興趣。)還有許多類似的問題:在計劃建築物的使用壽命內,可能發生的最強地震的震中強度是多少?或者一座懸索橋需要承受的最強風速是多少?所有這些情況都可以用相同的方式建模。在時間t時,感興趣的量X(無論是水位還是風速)是一個隨機變數。對於某個範圍內的t,X的最大值可以說些什麼?一組隨機變數(X_t),其中t屬於某個索引集T,稱為隨機過程,本書的主題是研究某些隨機過程的上確界,並更精確地尋找量EsupX的上界和下界。(0.1) 由於T可能是不可數的,因此在定義這個量時需要謹慎。對於任何合理的Esup X的定義,我們有
EsupX = sup{EsupX; F∈T, F有限}, (0.2)
這是一個我們將作為量Esup X的定義的等式。t∈T因此,對於估計量(0的關鍵情況。