A Course on Small Area Estimation and Mixed Models - Methods, Theory and Applications in R (Hardcover, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Statistics for Social and Behavioral Sciences
Release date:	March 2021
First published:	2021
Authors:	Domingo Morales • Maria Dolores Esteban • Agustin Perez • Tomas Hobza
Dimensions:	235 x 155 x 36mm (L x W x T)
Format:	Hardcover
Pages:	599
Edition:	1st ed. 2021
ISBN-13:	978-3-03-063756-9
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Social sciences > Sociology, social studies > Social research & statistics > General Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software
LSN:	3-03-063756-5
Barcode:	9783030637569

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