Language:
English
繁體中文
Help
圖資館首頁
Login
Back
to Search results for
[ author_sort:"chen, jiahua." ]
Switch To:
Labeled
|
MARC Mode
|
ISBD
Statistical inference under mixture models
Record Type:
Electronic resources : Monograph/item
Title/Author:
Statistical inference under mixture modelsby Jiahua Chen.
Author:
Chen, Jiahua.
Published:
Singapore :Springer Nature Singapore :2023.
Description:
xiv, 327 p. :illustrations, digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
Mathematical statistics.
Online resource:
https://doi.org/10.1007/978-981-99-6141-2
ISBN:
9789819961412$q(electronic bk.)
Statistical inference under mixture models
Chen, Jiahua.
Statistical inference under mixture models
[electronic resource] /by Jiahua Chen. - Singapore :Springer Nature Singapore :2023. - xiv, 327 p. :illustrations, digital ;24 cm. - ICSA book series in statistics,2199-0999. - ICSA book series in statistics..
1. Introduction to mixture models -- 2. Nonparametric MLE and its consistency -- 3. Maximum likelihood estimation under finite mixture models -- 4. Estimation under finite normal mixture models -- 5. Consistent estimation under finite Gamma mixture -- 6. Geometric properties of nonparametric MLE and numerical solutions -- 7. EM-algorithm -- 8. Rate of convergence -- 9. Test of homogeneity -- 10. Likelihood ratio test for homogeneity -- 11. Modified likelihood ratio test -- 12. Modified likelihood ratio test for higher order -- 13 EM-test for homogeneity -- 14 EM-test for higher order -- 15 EM-test for univariate finite Gaussian mixture models -- 16 Order selection of the finite mixture models -- 17 A few key probability theory results employed -- References.
This book puts its weight on theoretical issues related to finite mixture models. It shows that a good applicant, is an applicant who understands the issues behind each statistical method. This book is intended for applicants whose interests include some understanding of the procedures they are using, while they do not have to read the technical derivations. At the same time, many researchers find most theories and techniques necessary for the development of various statistical methods, without chasing after one set of research papers, after another. Even though the book emphasizes the theory, it provides accessible numerical tools for data analysis. Readers with strength in developing statistical software, may find it useful.
ISBN: 9789819961412$q(electronic bk.)
Standard No.: 10.1007/978-981-99-6141-2doiSubjects--Topical Terms:
181877
Mathematical statistics.
LC Class. No.: QA276 / .C44 2023
Dewey Class. No.: 519.5
Statistical inference under mixture models
LDR
:02540nmm a2200337 a 4500
001
654064
003
DE-He213
005
20231122162621.0
006
m d
007
cr nn 008maaau
008
240426s2023 si s 0 eng d
020
$a
9789819961412$q(electronic bk.)
020
$a
9789819961399$q(paper)
024
7
$a
10.1007/978-981-99-6141-2
$2
doi
035
$a
978-981-99-6141-2
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA276
$b
.C44 2023
072
7
$a
PBT
$2
bicssc
072
7
$a
MAT029000
$2
bisacsh
072
7
$a
PBT
$2
thema
082
0 4
$a
519.5
$2
23
090
$a
QA276
$b
.C518 2023
100
1
$a
Chen, Jiahua.
$3
661251
245
1 0
$a
Statistical inference under mixture models
$h
[electronic resource] /
$c
by Jiahua Chen.
260
$a
Singapore :
$b
Springer Nature Singapore :
$b
Imprint: Springer,
$c
2023.
300
$a
xiv, 327 p. :
$b
illustrations, digital ;
$c
24 cm.
490
1
$a
ICSA book series in statistics,
$x
2199-0999
505
0
$a
1. Introduction to mixture models -- 2. Nonparametric MLE and its consistency -- 3. Maximum likelihood estimation under finite mixture models -- 4. Estimation under finite normal mixture models -- 5. Consistent estimation under finite Gamma mixture -- 6. Geometric properties of nonparametric MLE and numerical solutions -- 7. EM-algorithm -- 8. Rate of convergence -- 9. Test of homogeneity -- 10. Likelihood ratio test for homogeneity -- 11. Modified likelihood ratio test -- 12. Modified likelihood ratio test for higher order -- 13 EM-test for homogeneity -- 14 EM-test for higher order -- 15 EM-test for univariate finite Gaussian mixture models -- 16 Order selection of the finite mixture models -- 17 A few key probability theory results employed -- References.
520
$a
This book puts its weight on theoretical issues related to finite mixture models. It shows that a good applicant, is an applicant who understands the issues behind each statistical method. This book is intended for applicants whose interests include some understanding of the procedures they are using, while they do not have to read the technical derivations. At the same time, many researchers find most theories and techniques necessary for the development of various statistical methods, without chasing after one set of research papers, after another. Even though the book emphasizes the theory, it provides accessible numerical tools for data analysis. Readers with strength in developing statistical software, may find it useful.
650
0
$a
Mathematical statistics.
$3
181877
650
1 4
$a
Statistical Theory and Methods.
$3
274054
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer Nature eBook
830
0
$a
ICSA book series in statistics.
$3
725077
856
4 0
$u
https://doi.org/10.1007/978-981-99-6141-2
950
$a
Mathematics and Statistics (SpringerNature-11649)
based on 0 review(s)
ALL
電子館藏
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
000000236176
電子館藏
1圖書
電子書
EB QA276 .C518 2023 2023
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Multimedia file
https://doi.org/10.1007/978-981-99-6141-2
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login