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Asymptotics for EBLUPs: Nested Error Regression Models
Journal of the American Statistical Association, 2021In this paper we derive the asymptotic distribution of estimated best linear unbiased predictors (EBLUPs) of the random effects in a nested error regression model. Under very mild conditions which do not require the assumption of normality, we show that asymptotically the distribution of the EBLUPs as both the number of clusters and the cluster sizes ...
Ziyang Lyu, A.H. Welsh
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Prediction in an Unbalanced Nested Error Components Panel Data Model
Journal of Forecasting, 2013ABSTRACTThis paper derives the best linear unbiased predictor for an unbalanced nested error components panel data model. This predictor is useful in many econometric applications that are usually based on unbalanced panel data and have a nested (hierarchical) structure.
Badi H. Baltagi
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Calibrating Nested Sensor Arrays With Model Errors
IEEE Transactions on Antennas and Propagation, 2014We consider the problem of direction of arrival (DOA) estimation based on a nonuniform linear nested array, which is known to provide $O(N^2)$ degrees of freedom (DOFs) using only $N$ sensors. Both subspace-based and sparsity-based algorithms require certain modeling assumptions, e.g., exactly known array geometry, including sensor gain and ...
Keyong Han, Peng Yang 0006, Arye Nehorai
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Nested Error Regression Models
2020This chapter deals with the estimation of the regression and variance components’ parameters of the nested error regression model. It describes three fitting methods for calculating maximum likelihood, residual maximum likelihood, and method of moments estimators.
Domingo Morales +3 more
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On Testing Linear Hypothesis in a Nested Error Regression Model
Communications in Statistics - Theory and Methods, 2010Consider the problem of testing the linear hypothesis on regression coefficients in the nested error regression model. The standard F-test statistic based on the ordinary least squares (OLS) estimator has the serious shortcoming that its type I error rates (sizes) are much larger than nominal significance levels, because the covariance matrix of data ...
Tatsuya Kubokawa
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Prediction in heteroscedastic nested error regression models with random dispersions [PDF]
Statistica Sinica, 2016 The paper concerns small-area estimation in the heteroscedastic nested error regression (HNER) model which assumes that the within-area variances are different among areas. Although HNER is useful for analyzing data where the within-area variation changes from area to area, it is difficult to provide good estimates for the error variances because of ...
Tatsuya Kubokawa +3 more
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BLUP in the nested panel regression model with serially correlated errors
Computational Statistics and Data Analysis, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Myoungshic Jhun, Seuck Heun Song
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A nested error regression model with high-dimensional parameter for small area estimation
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2023 Abstract In this paper, we propose a flexible nested error regression small area model with high-dimensional parameter that incorporates heterogeneity in regression coefficients and variance components. We develop a new robust small area-specific estimating equations method that allows appropriate pooling of a large number of areas in ...
Nicola Salvati, Partha Lahiri
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EBPs Under Nested Error Regression Models
2020This chapter treats the problem of predicting linear combinations of components of a finite population random vector. The linear parameters have the form of weighted sums with known positive or null weights. By assuming that the population target vector follows a nested error regression model, this chapter introduces empirical best linear unbiased ...
Domingo Morales +3 more
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The unbalanced nested error component regression model
Journal of Econometrics, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baltagi, Badi H. +2 more
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