Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): applications to tomography
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منابع مشابه
Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): applications to tomography
Many estimators in signal processing problems are defined implicitly as the maximum of some objective function. Examples of implicitly defined estimators include maximum likelihood, penalized likelihood, maximum a posteriori, and nonlinear least squares estimation. For such estimators, exact analytical expressions for the mean and variance are usually unavailable. Therefore, investigators usual...
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Many estimators in signal processing problems are defined implicitly as the maximum of some objective function. Examples of implicitly defined estimators include maximum likelihood, penalized likelihood, maximum a posteriori, and nonlinear least squares estimation. For such estimators, exact analytical expressions for the mean and variance are usually unavailable. Therefore, investigators usual...
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Confidence intervals based on penalized maximum likelihood estimators such as the LASSO, adaptive LASSO, and hard-thresholding are analyzed. In the known-variance case, the finite-sample coverage properties of such intervals are determined and it is shown that symmetric intervals are the shortest. The length of the shortest intervals based on the hard-thresholding estimator is larger than the l...
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ژورنال
عنوان ژورنال: IEEE Transactions on Image Processing
سال: 1996
ISSN: 1057-7149,1941-0042
DOI: 10.1109/83.491322