WebRobust Small Area Estimation Using Penalized Spline Mixed Models J. N. K. Rao, S. K. Sinha and M. Roknossadati School of Mathematics and Statistics, Carleton University, Ottawa, Canada K1S 5B6 Abstract Small area estimation has been extensively studied under linear mixed models. In particular, empirical best linear unbiased prediction (EBLUP ... WebMar 9, 2024 · Small area estimation (SAE) is a statistical technique used to enhance data in a specific area (i.e., geographic, demographic) with data not confined to that area (Rao, …
Spatial robust small area estimation SpringerLink
WebOct 25, 2024 · Robust Small Area Estimation: a Vignette Tobias Schoch December 29, 2011: rsae 0.1-4 Contents 1 Introduction2 2 Getting started2 3 Setting up a model3 ... (Robust) Estimation Having set up our model, we consider estimating the parameters of the Gaussian core model by di erent methods. All tting is done using the following workhorse function maximus tax fort worth tx
Estimation of small area proportions under a bivariate logistic …
WebOct 24, 2024 · This paper introduces a general area-level model-based formulation to small area estimation based on generalized linear mixed models. By applying an optimization algorithm to the Laplace... WebSpatial robust small area estimation 657 solve the robust equations and defined the estimates at convergence to be the robust ML-estimatorsβˆ ψ andθˆ ψ ofβ andθ respectively,wherethesuperscriptψ standsfor influence function ψ (e.g. Huber function). Sinha and Rao (2009) then used βˆ ψ and θˆ ψ for the estimation of the robust area- WebFeb 2, 2014 · This presents a semiparametric approach to small area prediction that reduces the need for parametric assumptions and allows for outlier robust estimation. The results … hernie b antonio