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
Robust multivariate analysis
~
Olive, David J.
FindBook
Google Book
Amazon
博客來
Robust multivariate analysis
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Robust multivariate analysis/ by David J. Olive.
作者:
Olive, David J.
出版者:
Cham :Springer International Publishing : : 2017.,
面頁冊數:
xvi, 501 p. :ill., digital ;24 cm.
內容註:
Introduction -- Multivariate Distributions -- Elliptically Contoured Distributions -- MLD Estimators -- DD Plots and Prediction Regions -- Principal Component Analysis -- Canonical Correlation Analysis -- Discrimination Analysis -- Hotelling's T^2 Test -- MANOVA -- Factor Analysis -- Multivariate Linear Regression -- Clustering -- Other Techniques -- Stuff for Students.
Contained By:
Springer eBooks
標題:
Multivariate analysis. -
電子資源:
http://dx.doi.org/10.1007/978-3-319-68253-2
ISBN:
9783319682532
Robust multivariate analysis
Olive, David J.
Robust multivariate analysis
[electronic resource] /by David J. Olive. - Cham :Springer International Publishing :2017. - xvi, 501 p. :ill., digital ;24 cm.
Introduction -- Multivariate Distributions -- Elliptically Contoured Distributions -- MLD Estimators -- DD Plots and Prediction Regions -- Principal Component Analysis -- Canonical Correlation Analysis -- Discrimination Analysis -- Hotelling's T^2 Test -- MANOVA -- Factor Analysis -- Multivariate Linear Regression -- Clustering -- Other Techniques -- Stuff for Students.
This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author's website.
ISBN: 9783319682532
Standard No.: 10.1007/978-3-319-68253-2doiSubjects--Topical Terms:
517467
Multivariate analysis.
LC Class. No.: QA278
Dewey Class. No.: 519.535
Robust multivariate analysis
LDR
:02402nmm a2200325 a 4500
001
2112550
003
DE-He213
005
20180522162113.0
006
m d
007
cr nn 008maaau
008
180719s2017 gw s 0 eng d
020
$a
9783319682532
$q
(electronic bk.)
020
$a
9783319682518
$q
(paper)
024
7
$a
10.1007/978-3-319-68253-2
$2
doi
035
$a
978-3-319-68253-2
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA278
072
7
$a
PBT
$2
bicssc
072
7
$a
PBWL
$2
bicssc
072
7
$a
MAT029000
$2
bisacsh
082
0 4
$a
519.535
$2
23
090
$a
QA278
$b
.O48 2017
100
1
$a
Olive, David J.
$3
2068591
245
1 0
$a
Robust multivariate analysis
$h
[electronic resource] /
$c
by David J. Olive.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2017.
300
$a
xvi, 501 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
Introduction -- Multivariate Distributions -- Elliptically Contoured Distributions -- MLD Estimators -- DD Plots and Prediction Regions -- Principal Component Analysis -- Canonical Correlation Analysis -- Discrimination Analysis -- Hotelling's T^2 Test -- MANOVA -- Factor Analysis -- Multivariate Linear Regression -- Clustering -- Other Techniques -- Stuff for Students.
520
$a
This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author's website.
650
0
$a
Multivariate analysis.
$3
517467
650
1 4
$a
Mathematics.
$3
515831
650
2 4
$a
Probability Theory and Stochastic Processes.
$3
891080
650
2 4
$a
Statistical Theory and Methods.
$3
891074
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-68253-2
950
$a
Mathematics and Statistics (Springer-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
W9324823
電子資源
11.線上閱覽_V
電子書
EB QA278
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