Probability Theory 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Probability Theory

简体网页||繁体网页
Henry Teicher, Yuan Shih Chow 作者
Springer
译者
2008-5-23 出版日期
512 页数
GBP 53.99 价格
Paperback
Springer Texts in Statistics 丛书系列
9780387406077 图书编码

Probability Theory 在线电子书 图书标签: 数学  概率  Probability  经典图书  新水  工程概论论  Statistics  Mathematics   


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发表于2024-11-21


Probability Theory 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Probability Theory 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Probability Theory 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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pay attention to this book because it appears on my teacher's reference to lectures many times.

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pay attention to this book because it appears on my teacher's reference to lectures many times.

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各种奇巧淫技啊。

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pay attention to this book because it appears on my teacher's reference to lectures many times.

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各种奇巧淫技啊。

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Probability Theory 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Probability Theory 在线电子书 图书描述

Comprising the major theorems of probability theory and the measure theoretical foundations of the subject, the main topics treated here are independence, interchangeability, and martingales. Particular emphasis is placed upon stopping times, both as tools in proving theorems and as objects of interest themselves. No prior knowledge of measure theory is assumed and a unique feature of the book is the combined presentation of measure and probability. It is easily adapted for graduate students familiar with measure theory using the guidelines given. Special features include: - A comprehensive treatment of the law of the iterated logarithm - The Marcinklewicz-Zygmund inequality, its extension to martingales and applications thereof - Development and applications of the second moment analogue of Walds equation - Limit theorems for martingale arrays; the central limit theorem for the interchangeable and martingale cases; moment convergence in the central limit theorem - Complete discussion, including central limit theorem, of the random casting of r balls into n cells - Recent martingale inequalities - Cram r-L vy theorem and factor-closed families of distributions.

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