語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Biased sampling, over-identified par...
~
Qin, Jing.
Biased sampling, over-identified parameter problems and beyond
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Biased sampling, over-identified parameter problems and beyond/ by Jing Qin.
作者:
Qin, Jing.
出版者:
Singapore :Springer Singapore : : 2017.,
面頁冊數:
xvi, 624 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
標題:
Sampling (Statistics) -
電子資源:
http://dx.doi.org/10.1007/978-981-10-4856-2
ISBN:
9789811048562
Biased sampling, over-identified parameter problems and beyond
Qin, Jing.
Biased sampling, over-identified parameter problems and beyond
[electronic resource] /by Jing Qin. - Singapore :Springer Singapore :2017. - xvi, 624 p. :ill., digital ;24 cm. - ICSA book series in statistics,2199-0980. - ICSA book series in statistics..
Chapter 1. Some Examples on Biased Sampling Problems -- Chapter 2. Some Results in Parametric Likelihood and Estimating Functions -- Chapter 3. Nonparametric Maximum Likelihood Estimation and Empirical Likelihood Method -- Chapter 4. General Results in Multiple Samples Biased Sampling Problems with Applications in Case and Control and Genetic Epidemiology -- Chapter 5. Outcome Dependent Sampling Problems -- Chapter 6. Missing Data Problem and Causal Inference -- Chapter 7. Applications of Exponential Tilting Models in Finite Mixture Models -- Chapter 8. Applications of Empirical Likelihood Methods in Survey Sampling -- Chapter 9. Some Other Topics.
This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others.
ISBN: 9789811048562
Standard No.: 10.1007/978-981-10-4856-2doiSubjects--Topical Terms:
527722
Sampling (Statistics)
LC Class. No.: QA276.6
Dewey Class. No.: 519.52
Biased sampling, over-identified parameter problems and beyond
LDR
:02615nam a2200337 a 4500
001
905835
003
DE-He213
005
20180118103128.0
006
m d
007
cr nn 008maaau
008
190308s2017 si s 0 eng d
020
$a
9789811048562
$q
(electronic bk.)
020
$a
9789811048548
$q
(paper)
024
7
$a
10.1007/978-981-10-4856-2
$2
doi
035
$a
978-981-10-4856-2
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA276.6
072
7
$a
PBT
$2
bicssc
072
7
$a
K
$2
bicssc
072
7
$a
BUS061000
$2
bisacsh
082
0 4
$a
519.52
$2
23
090
$a
QA276.6
$b
.Q1 2017
100
1
$a
Qin, Jing.
$3
1173245
245
1 0
$a
Biased sampling, over-identified parameter problems and beyond
$h
[electronic resource] /
$c
by Jing Qin.
260
$a
Singapore :
$c
2017.
$b
Springer Singapore :
$b
Imprint: Springer,
300
$a
xvi, 624 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
ICSA book series in statistics,
$x
2199-0980
505
0
$a
Chapter 1. Some Examples on Biased Sampling Problems -- Chapter 2. Some Results in Parametric Likelihood and Estimating Functions -- Chapter 3. Nonparametric Maximum Likelihood Estimation and Empirical Likelihood Method -- Chapter 4. General Results in Multiple Samples Biased Sampling Problems with Applications in Case and Control and Genetic Epidemiology -- Chapter 5. Outcome Dependent Sampling Problems -- Chapter 6. Missing Data Problem and Causal Inference -- Chapter 7. Applications of Exponential Tilting Models in Finite Mixture Models -- Chapter 8. Applications of Empirical Likelihood Methods in Survey Sampling -- Chapter 9. Some Other Topics.
520
$a
This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others.
650
0
$a
Sampling (Statistics)
$3
527722
650
1 4
$a
Statistics.
$3
556824
650
2 4
$a
Statistics for Business/Economics/Mathematical Finance/Insurance.
$3
669275
650
2 4
$a
Applications of Mathematics.
$3
669175
650
2 4
$a
Economic Theory/Quantitative Economics/Mathematical Methods.
$3
1069071
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
ICSA book series in statistics.
$3
1067975
856
4 0
$u
http://dx.doi.org/10.1007/978-981-10-4856-2
950
$a
Mathematics and Statistics (Springer-11649)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入