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A modified nested-error regression model for small area estimation

Statistics, 2013
A nested-error regression model having both fixed and random effects is introduced to estimate linear parameters of small areas. The model is applicable to data having a proportion of domains where the variable of interest cannot be described by a standard linear mixed model.
Maria Dolores Esteban, Domingo Morales
exaly   +2 more sources

Calibrating Nested Sensor Arrays With Model Errors

IEEE Transactions on Antennas and Propagation, 2014
We 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
openaire   +1 more source

Prediction in heteroscedastic nested error regression models with random dispersions [PDF]

open access: possibleStatistica 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
openaire   +1 more source

Nested Error Regression Models

2020
This 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
openaire   +1 more source

EBPs Under Nested Error Regression Models

2020
This 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
openaire   +1 more source

The unbalanced nested error component regression model

Journal of Econometrics, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baltagi, Badi H.   +2 more
openaire   +1 more source

Inference for nested error linear regression models with unequal error variances

Journal of Statistical Planning and Inference, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yu, M., Rao, J. N. K.
openaire   +2 more sources

Fast and robust estimators of variance components in the nested error model

Statistics and Computing, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Betsabé Pérez   +4 more
openaire   +1 more source

Error Normality Testing in a Model of Two‐Way Nested Classification

Biometrical Journal, 1994
AbstractThe paper deals with the construction of a normality test for the verification of the assumption about normal distribution of random errors in a fixed model of two‐way nested classification. For this purpose adequate linear transformations and orthogonal observable random vectors have been presented.
Brzeskwiniewicz, Henryk   +1 more
openaire   +2 more sources

Empirical best prediction under a nested error model with log transformation [PDF]

open access: yesAnnals of Statistics, 2018
In regression models involving economic variables such as income, log transformation is typically taken to achieve approximate normality and stabilize the variance.
Isabel Molina, Nirian Martin
exaly   +2 more sources

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