Abstract A variety of data is geographic interest but not available at a small area level from large-scale national sample surveys. Small estimation can be used to estimate parameters target variables detailed geographical scales based on relationships between the and relevant auxiliary information. proportions topic great in many fields study, where binary are diffused, such as labour force, b...

Abstract Socioeconomic indicators play a crucial role in monitoring political actions over time and across regions. Income-based such as the median income of sub-populations can provide information on impact measures, e.g., poverty reduction. Regional is usually published an aggregated level. Due to small sample sizes, these regional aggregates are often associated with large standard errors or...

Best linear unbiased prediction is well known for its wide range of applications including small area estimation. While the theory is well established for mixed linear models and under normality of the error and mixing distributions, the literature is sparse for nonlinear mixed models under nonnormality of the error or of the mixing distributions. This article develops a resampling based unifie...

• In this paper it is proposed a spatio-temporal area level linear mixed model involving spatially correlated and temporally autocorrelated random effects. An empirical best linear unbiased predictor (EBLUP) for small area parameters has been obtained under the proposed model. Using previous research in this area, analytical and bootstrap estimators of the mean squared prediction error (MSPE) o...

Nonparametric regression is widely used as a method of characterising a non-linear relationship between a variable of interest and a set of covariates. Practical application of nonparametric regression methods in the field of small area estimation is fairly recent, and has so far focussed on the use of empirical best linear unbiased prediction under a model that combines a penalized spline (p-s...

Introduction Multivariate Fay–Herriot models for estimating small area indicators are introduced. Among the available procedures for fitting linear mixed models, the residual maximum likelihood (REML) is employed. The empirical best predictor (EBLUP) of the vector of area means is derived. An approximation to the matrix of mean squared crossed prediction errors (MSE) is given and four MSE estim...