Small area estimation of expenditure means and ratios under a unit-level bivariate linear mixed model

2020 ◽  
pp. 1-26
Author(s):  
María Dolores Esteban ◽  
María José Lombardía ◽  
Esther López-Vizcaíno ◽  
Domingo Morales ◽  
Agustín Pérez
Keyword(s):  
Small Area ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Small Area Estimation ◽  
Area Estimation ◽  
Unit Level

scholarly journals Small Area Estimation on Zero-Inflated Data Using Frequentist and Bayesian Approach

2020 ◽  
Vol 18 (1) ◽  
pp. 2-22
Author(s):  
Kusman Sadik ◽  
Rahma Anisa ◽  
Euis Aqmaliyah
Keyword(s):  
Bayesian Approach ◽  
Small Area ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Small Area Estimation ◽  
Prediction Method ◽  
Linear Unbiased Prediction ◽  
Area Estimation ◽  
Best Linear Unbiased ◽  
Sr Method

The most commonly used method of small area estimation (SAE) is the empirical best linear unbiased prediction method based on a linear mixed model. However, it is not appropriate in the case of the zero-inflated target variable with a mixture of zeros and continuously distributed positive values. Therefore, various model-based SAE methods for zero-inflated data are developed, such as the Frequentist approach and the Bayesian approach. Both approaches are compared with the survey regression (SR) method which ignores the presence of zero-inflation in the data. The results show that the two SAE approaches for zero-inflated data are capable to yield more accurate area mean estimates than the SR method.

Sae: A Stata Package For Unit Level Small Area Estimation

2018 ◽  
Author(s):  
Minh Cong Nguyen ◽  
Paul Corral ◽  
Joao Pedro Azevedo ◽  
Qinghua Zhao
Keyword(s):  
Small Area ◽  
Small Area Estimation ◽  
Area Estimation ◽  
Unit Level

A generalized mixed model for skewed distributions applied to small area estimation

Test ◽  
2018 ◽  
Vol 28 (2) ◽  
pp. 565-597 ◽  
Author(s):  
Monique Graf ◽  
J. Miguel Marín ◽  
Isabel Molina
Keyword(s):  
Small Area ◽  
Mixed Model ◽  
Small Area Estimation ◽  
Skewed Distributions ◽  
Area Estimation

scholarly journals Analysis of area level and unit level models for small area estimation in forest inventories assisted with LiDAR auxiliary information

PLoS ONE ◽  
2017 ◽  
Vol 12 (12) ◽  
pp. e0189401 ◽  
Author(s):  
Francisco Mauro ◽  
Vicente J. Monleon ◽  
Hailemariam Temesgen ◽  
Kevin R. Ford
Keyword(s):  
Small Area ◽  
Small Area Estimation ◽  
Auxiliary Information ◽  
Area Estimation ◽  
Unit Level ◽  
Forest Inventories
Sign in / Sign up

Export Citation Format

Share Document