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MOST INFORMATIVE COMPONENT ANALYSIS:

Jing, Yaping ; Lei, Hong ; Xia, Yingcun
Statistica Sinica. 24 (2014) 3 - p. 1195-1214 , 2014

Link: https://www.jstor.org/stable/24310984

RT Journal
T1 <Title>MOST INFORMATIVE COMPONENT ANALYSIS</Title>

UL https://suche.suub.uni-bremen.de/peid=jstor-24310984&Exemplar=1&LAN=DE
				
A1 Jing, Yaping
A1 Lei, Hong
A1 Xia, Yingcun
PB Institute of Statistical Science, Academia Sinica and International Chinese Statistical Association
YR 2014
SN 1017-0405
SN 1996-8507
K1 Mathematics
K1 Mathematical analysis
K1 Principal components analysis
K1 Applied mathematics
K1 Statistics
K1 Applied statistics
K1 Inferential statistics
K1 Statistical estimation
K1 Estimation methods
K1 Estimators
K1 Physical sciences
K1 Earth sciences
K1 Geology
K1 Mineralogy
K1 Minerals
K1 Mica
K1 Applied sciences
K1 Computer science
K1 Artificial intelligence
K1 Machine learning
K1 Dimensionality reduction
K1 Information science
K1 Information analysis
K1 Data analysis
K1 Regression analysis
K1 Linear regression
K1 Data products
K1 Datasets
K1 Mathematical procedures
K1 Approximation
K1 Preliminary estimates
K1 Pure mathematics
K1 Linear algebra
K1 Vector analysis
K1 Mathematical vectors
K1 Eigenvectors
JF Statistica Sinica
VO 24
IS 3
SP 1195
OP 1214
LK http://dx.doi.org/https://www.jstor.org/stable/24310984
DO https://www.jstor.org/stable/24310984
SF ELIB - SuUB Bremen

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