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Uniformly best biased estimators in non-bayesian parameter estimation
Koby Todros
,
Joseph Tabrikian
School of Electrical and Computer Engineering
Department of Electrical & Computer Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
9
Scopus citations
Overview
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Dive into the research topics of 'Uniformly best biased estimators in non-bayesian parameter estimation'. Together they form a unique fingerprint.
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Mathematics
Parameter Estimation
100%
Bayesian
100%
Biased Estimator
100%
Maximum Likelihood Estimator
16%
Parameter Space
16%
Variance
16%
Unbiased Estimator
16%
Closed Form
16%
Necessary and Sufficient Condition
16%
Mean Square Error
16%
Keyphrases
Non-Bayesian Estimation
100%
Biased Estimator
100%
Parameter Space
16%
Maximum Likelihood Estimator
16%
Minimum Mean Square Error
16%
Closed-form Expression
16%
Nonlinear Estimation Problems
16%
Non-Bayesian
16%
Mean-square-error Performance
16%
Optimal Bias
16%
Uniformly Minimum Variance Unbiased Estimator
16%