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A class of general adjusted maximum likelihood methods for desirable mean squared error estimation of EBLUP under the Fay–Herriot small area model
Masayo Y. Hirose
Research output
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Contribution to journal
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Article
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peer-review
4
Citations (Scopus)
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Dive into the research topics of 'A class of general adjusted maximum likelihood methods for desirable mean squared error estimation of EBLUP under the Fay–Herriot small area model'. Together they form a unique fingerprint.
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Mathematics
Squared Prediction Error
100%
Classes
55%
Linear Unbiased Prediction
55%
Maximum Likelihood Method
33%
Order
22%
Parameters
22%
Smaller Area
22%
Variance Model
22%
Measures
11%
Unbiased Estimator
11%
Functional Form
11%
Inference
11%
Simulation Study
11%
Mean Squared Error Estimation
11%
Computer Science
Classes
55%
Maximum Likelihood Method
33%
Desired Property
22%
Monte Carlo Simulation
22%
Simulation Mode
11%
Error Estimation
11%
Relationships
11%
Simulation Study
11%
Functional Form
11%
Unbiased Estimator
11%
Economics, Econometrics and Finance
Estimation Theory
88%
Order
22%