//--> //--> //-->
Toggle navigation
Logout
Change account settings
EN
DE
ES
FR
A-Z
Beta
About EconBiz
News
Thesaurus (STW)
Research Skills
Help
EN
DE
ES
FR
My account
Logout
Change account settings
Login
Publications
Events
Your search terms
Search
Retain my current filters
~person:"Sun, Xiaoqian"
Search options
All Fields
Title
Exact title
Subject
Author
Institution
ISBN/ISSN
Published in...
Publisher
Open Access only
Advanced
Search history
My EconBiz
Favorites
Loans
Reservations
Fines
You are here:
Home
Search: subject:"invariant Haar measure"
Narrow search
Delete all filters
| 1 applied filter
Year of publication
From:
To:
Subject
All
Jeffreys prior
2
Bartlett decomposition
1
Bayesian estimator
1
Best equivariant estimator
1
Cholesky decomposition
1
Covariance matrix
1
Inadmissibility
1
Invariant Haar measure
1
Maximum likelihood estimator
1
Reference prior
1
Staircase pattern data
1
Star-shape model
1
covariance matrix
1
entropy loss
1
inadmissibility
1
invariant Haar measure
1
maximum likelihood estimator
1
precision matrix
1
reference prior
1
symmetric loss
1
more ...
less ...
Online availability
All
Undetermined
2
Type of publication
All
Article
2
Language
All
Undetermined
2
Author
All
Sun, Xiaoqian
Sun, Dongchu
2
He, Daojiang
1
Xu, Kai
1
Published in...
All
Annals of the Institute of Statistical Mathematics
2
Source
All
RePEc
2
Showing
1
-
2
of
2
Sort
relevance
articles prioritized
date (newest first)
date (oldest first)
1
Estimation of a Multivariate Normal Covariance Matrix with Staircase Pattern Data
Sun, Xiaoqian
;
Sun, Dongchu
- In:
Annals of the Institute of Statistical Mathematics
59
(
2007
)
2
,
pp. 211-233
Persistent link: https://www.econbiz.de/10005616452
Saved in:
2
Estimation of the multivariate normal precision and covariance matrices in a star-shape model
Sun, Dongchu
;
Sun, Xiaoqian
- In:
Annals of the Institute of Statistical Mathematics
57
(
2005
)
3
,
pp. 455-484
Persistent link: https://www.econbiz.de/10005616411
Saved in:
Results per page
10
25
50
100
250
A service of the
zbw
×
Loading...
//-->