語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Measure, probability and functional ...
~
Geiss, Hannah.
FindBook
Google Book
Amazon
博客來
Measure, probability and functional analysis
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Measure, probability and functional analysis/ by Hannah Geiss, Stefan Geiss.
作者:
Geiss, Hannah.
其他作者:
Geiss, Stefan.
出版者:
Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:
xx, 443 p. :ill. (chiefly color), digital ;24 cm.
Contained By:
Springer Nature eBook
標題:
Probabilities. -
電子資源:
https://doi.org/10.1007/978-3-031-84067-8
ISBN:
9783031840678
Measure, probability and functional analysis
Geiss, Hannah.
Measure, probability and functional analysis
[electronic resource] /by Hannah Geiss, Stefan Geiss. - Cham :Springer Nature Switzerland :2025. - xx, 443 p. :ill. (chiefly color), digital ;24 cm. - Universitext,2191-6675. - Universitext..
This textbook offers a self-contained introduction to probability, covering all topics required for further study in stochastic processes and stochastic analysis, as well as some advanced topics at the interface between probability and functional analysis. The initial chapters provide a rigorous introduction to measure theory, with a special focus on probability spaces. Next, Lebesgue integration theory is developed in full detail covering the main methods and statements, followed by the important limit theorems of probability. Advanced limit theorems, such as the Berry-Esseen Theorem and Stein's method, are included. The final part of the book explores interactions between probability and functional analysis. It includes an introduction to Banach function spaces, such as Lorentz and Orlicz spaces, and to random variables with values in Banach spaces. The Itô-Nisio Theorem, the Strong Law of Large Numbers in Banach spaces, and the Bochner, Pettis, and Dunford integrals are presented. As an application, Brownian motion is rigorously constructed and investigated using Banach function space methods. Based on courses taught by the authors, this book can serve as the main text for a graduate-level course on probability, and each chapter contains a collection of exercises. The unique combination of probability and functional analysis, as well as the advanced and original topics included, will also appeal to researchers working in probability and related fields.
ISBN: 9783031840678
Standard No.: 10.1007/978-3-031-84067-8doiSubjects--Topical Terms:
518889
Probabilities.
LC Class. No.: QA273
Dewey Class. No.: 519.2
Measure, probability and functional analysis
LDR
:02546nmm a2200349 a 4500
001
2409478
003
DE-He213
005
20250326115239.0
006
m d
007
cr nn 008maaau
008
260204s2025 sz s 0 eng d
020
$a
9783031840678
$q
(electronic bk.)
020
$a
9783031840661
$q
(paper)
024
7
$a
10.1007/978-3-031-84067-8
$2
doi
035
$a
978-3-031-84067-8
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA273
072
7
$a
PBT
$2
bicssc
072
7
$a
PBWL
$2
bicssc
072
7
$a
MAT029000
$2
bisacsh
072
7
$a
PBT
$2
thema
072
7
$a
PBWL
$2
thema
082
0 4
$a
519.2
$2
23
090
$a
QA273
$b
.G313 2025
100
1
$a
Geiss, Hannah.
$3
3782742
245
1 0
$a
Measure, probability and functional analysis
$h
[electronic resource] /
$c
by Hannah Geiss, Stefan Geiss.
260
$a
Cham :
$b
Springer Nature Switzerland :
$b
Imprint: Springer,
$c
2025.
300
$a
xx, 443 p. :
$b
ill. (chiefly color), digital ;
$c
24 cm.
490
1
$a
Universitext,
$x
2191-6675
520
$a
This textbook offers a self-contained introduction to probability, covering all topics required for further study in stochastic processes and stochastic analysis, as well as some advanced topics at the interface between probability and functional analysis. The initial chapters provide a rigorous introduction to measure theory, with a special focus on probability spaces. Next, Lebesgue integration theory is developed in full detail covering the main methods and statements, followed by the important limit theorems of probability. Advanced limit theorems, such as the Berry-Esseen Theorem and Stein's method, are included. The final part of the book explores interactions between probability and functional analysis. It includes an introduction to Banach function spaces, such as Lorentz and Orlicz spaces, and to random variables with values in Banach spaces. The Itô-Nisio Theorem, the Strong Law of Large Numbers in Banach spaces, and the Bochner, Pettis, and Dunford integrals are presented. As an application, Brownian motion is rigorously constructed and investigated using Banach function space methods. Based on courses taught by the authors, this book can serve as the main text for a graduate-level course on probability, and each chapter contains a collection of exercises. The unique combination of probability and functional analysis, as well as the advanced and original topics included, will also appeal to researchers working in probability and related fields.
650
0
$a
Probabilities.
$3
518889
650
0
$a
Measure theory.
$3
516951
650
1 4
$a
Probability Theory.
$3
3538789
650
2 4
$a
Functional Analysis.
$3
893943
650
2 4
$a
Measure and Integration.
$3
891263
700
1
$a
Geiss, Stefan.
$3
3782743
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
830
0
$a
Universitext.
$3
812115
856
4 0
$u
https://doi.org/10.1007/978-3-031-84067-8
950
$a
Mathematics and Statistics (SpringerNature-11649)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9514976
電子資源
11.線上閱覽_V
電子書
EB QA273
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入