Mixed-Effects Models and Small Area Estimation
This book provides a self-contained introduction of mixed-effects models and small area estimation techniques. In particular, it focuses on both introducing classical theory and reviewing the latest methods. First, basic issues of mixed-effects models, such as parameter estimation, random effects pr...
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| Những tác giả chính: | , |
|---|---|
| Tác giả của công ty: | |
| Định dạng: | Điện tử eBook |
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
|
| Phiên bản: | 1st ed. 2023. |
| Loạt: | JSS Research Series in Statistics,
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| Những chủ đề: | |
| Truy cập trực tuyến: | https://doi.org/10.1007/978-981-19-9486-9 |
| Các nhãn: |
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| 100 | 1 | |a Sugasawa, Shonosuke. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Mixed-Effects Models and Small Area Estimation |h [electronic resource] / |c by Shonosuke Sugasawa, Tatsuya Kubokawa. |
| 250 | |a 1st ed. 2023. | ||
| 264 | 1 | |a Singapore : |b Springer Nature Singapore : |b Imprint: Springer, |c 2023. | |
| 300 | |a 1 online resource (VIII, 121 p. 1 illus.). | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a JSS Research Series in Statistics, |x 2364-0065 | |
| 505 | 0 | |a Introduction -- General Mixed-Effects Models and BLUP -- Measuring Uncertainty of Predictors -- Basic mixed-effects Models for Small Area Estimation -- Hypothesis Tests and Variable Selection -- Advanced Theory of Basic Small Area Models -- Small Area Models for Non-normal Response Variables -- Extensions of Basic Small Area Models. | |
| 520 | |a This book provides a self-contained introduction of mixed-effects models and small area estimation techniques. In particular, it focuses on both introducing classical theory and reviewing the latest methods. First, basic issues of mixed-effects models, such as parameter estimation, random effects prediction, variable selection, and asymptotic theory, are introduced. Standard mixed-effects models used in small area estimation, known as the Fay-Herriot model and the nested error regression model, are then introduced. Both frequentist and Bayesian approaches are given to compute predictors of small area parameters of interest. For measuring uncertainty of the predictors, several methods to calculate mean squared errors and confidence intervals are discussed. Various advanced approaches using mixed-effects models are introduced, from frequentist to Bayesian approaches. This book is helpful for researchers and graduate students in fields requiring data analysis skills as well as in mathematical statistics. | ||
| 588 | |a Print version record. | ||
| 650 | 0 | |a Statistics . | |
| 650 | 1 | 4 | |a Applied Statistics. |
| 650 | 2 | 4 | |a Statistical Theory and Methods. |
| 650 | 2 | 4 | |a Bayesian Inference. |
| 650 | 2 | 4 | |a Bayesian Network. |
| 700 | 1 | |a Kubokawa, Tatsuya. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9789811994852 |
| 776 | 0 | 8 | |i Printed edition: |z 9789811994876 |
| 830 | 0 | |a JSS Research Series in Statistics, |x 2364-0065 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-981-19-9486-9 |
| 912 | |a ZDB-2-SMA | ||
| 912 | |a ZDB-2-SXMS | ||
| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||