A Course on Small Area Estimation and Mixed Models
Methods, Theory and Applications in R
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Beschreibung
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.
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.
Presents a rigorous mathematical description of statistical methodology for small area estimation Compares and contrasts various statistical methodologies Shows how to apply small area estimation techniques in surveys, providing the underlying R code
Autor*in
Domingo Morales
Themen in »A Course on Small Area Estimation and Mixed Models«
small area estimation linear mixed models generalized linear mixed model SAE R packages for SAE survey methodology estimation of socioeconomic indicators mean squared error estimation R code design-based estimation labor markets surveys living conditions surveys prediction theory linear models nested error regression models