A Course on Small Area Estimation and Mixed Models Methods, Theory and Applications in R
This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers un...
| Autor Corporativo: | |
|---|---|
| Otros Autores: | , , , |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing
2021.
|
| Edición: | 1st ed |
| Colección: | Springer eBooks.
Statistics for Social and Behavioral Sciences, |
| Acceso en línea: | Conectar con la versión electrónica |
| Ver en Universidad de Navarra: | https://innopac.unav.es/record=b45580388*spi |
| Sumario: | This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers understand how to develop new methodologies for small area estimation. It also includes numerous sample applications of small area estimation techniques. The underlying R code is provided in the text and applied to four datasets that mimic data from labor markets and living conditions surveys, where the socioeconomic indicators include the small area estimation of total unemployment, unemployment rates, average annual household incomes and poverty indicators. Given its scope, the book will be useful for master and PhD students, and for official and other applied statisticians. . |
|---|---|
| Descripción Física: | XX, 599 páginas : 373 ilustraciones, 10 ilustraciones (color) |
| Formato: | Forma de acceso: World Wide Web. |
| ISBN: | 9783030637576 |
