Functional Mixed Effects Model for Small Area Estimation

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Functional Mixed Effects Model for Small Area Estimation.

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fi...

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Supporting information for: “Functional Mixed Effects Model for Small Area Estimation”

Y = ZF bF +Wν + Υ, where W = (ZR,M0, · · · ,Mp) and ν = (bR, U 0 , U 1 , · · · , U p ) . Denote G = var(ν) = diag(cov(bR), In ⊗ Σu0, · · · , In ⊗ Σup) and cov(Y ) = Σ. Also, Σi = Σi(δ) = ZFicov(bR)Z Fi + cov(Ui0) + ∑p k=1 Diag(Xik) cov(Uik)Diag(Xik) + Ωi for i = 1, . . . , n. The estimator of bF is b̂F = (Z T FΣ ZF ) −1ZT FΣ −1Y and the predictor of ν is ν̂ = GW TΣ−1(Y − ZF b̂F ). The covariance m...

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ژورنال

عنوان ژورنال: Scandinavian Journal of Statistics

سال: 2016

ISSN: 0303-6898,1467-9469

DOI: 10.1111/sjos.12218