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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
Classes
55%
Functional Form
11%
Inference
11%
Linear Unbiased Prediction
55%
Maximum Likelihood Method
33%
Mean Squared Error Estimation
11%
Measures
11%
Order
22%
Parameters
22%
Simulation Study
11%
Smaller Area
22%
Squared Prediction Error
100%
Unbiased Estimator
11%
Variance Model
22%
Computer Science
Classes
55%
Desired Property
22%
Error Estimation
11%
Functional Form
11%
Maximum Likelihood Method
33%
Monte Carlo Simulation
22%
Relationships
11%
Simulation Mode
11%
Simulation Study
11%
Unbiased Estimator
11%
Economics, Econometrics and Finance
Estimation Theory
88%
Order
22%