Targeted maximum likelihood estimation
First Claim
1. A method for obtaining an estimator comprising:
- determining data;
determining an initial estimator descriptive of a first distribution of the data;
determining a target feature pertaining to the data; and
selectively modifying the initial estimator based on the target feature to determine a modified estimator, the modified estimator providing a second distribution of the data, wherein selectively modifying includes iteratively updating the modified estimator by using a previously determined modified estimator to provide the initial estimator for a subsequent iteration.
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Accused Products
Abstract
A method for obtaining an estimator for a distribution pertaining to a dataset is provided. In an illustrative embodiment, the method includes obtaining a dataset; determining a question pertaining to the data; determining an initial estimator descriptive of a distribution of the data; and selectively modifying the initial estimator based on the question, yielding a targeted estimator in response thereto. In a more specific embodiment, selectively modifying the initial estimator includes applying an additional equation and/or a fluctuation function to the initial estimator to yield the targeted estimator, wherein the additional equation or fluctuation function parameter (ε) causes the initial estimator to fluctuate or change as a function of the parameter. The fluctuation function is chosen so that when the parameter ε is set to zero, the initial estimator is not fluctuated. The targeted estimator and a fluctuation function may be employed in an accompanying targeted Bayesian method that involves mapping a prior distribution of a target feature to a posterior distribution of the target feature.
3 Citations
28 Claims
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1. A method for obtaining an estimator comprising:
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determining data; determining an initial estimator descriptive of a first distribution of the data; determining a target feature pertaining to the data; and selectively modifying the initial estimator based on the target feature to determine a modified estimator, the modified estimator providing a second distribution of the data, wherein selectively modifying includes iteratively updating the modified estimator by using a previously determined modified estimator to provide the initial estimator for a subsequent iteration. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method for obtaining an estimator comprising:
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determining data; determining an initial estimator descriptive of a first distribution of the data; determining a target feature pertaining to the data; selectively modifying the initial estimator based on the target feature to determine a modified estimator, the modified estimator providing a second distribution of the data; and determining multiple modified estimators from multiple initial estimators. - View Dependent Claims (13)
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14. A system configured to obtain an estimator of a distribution pertaining to data comprising:
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an initial estimator module configured to receive data and a target feature pertaining to the data, wherein the initial estimator module is configured to determine an initial estimator descriptive of a first distribution of the data; and a targeted estimator module coupled to the initial estimator module and configured to selectively modify the initial estimator based on the target feature to determine a modified estimator, the modified estimator providing a second distribution of the data, wherein the targeted estimator module is configured to provide a targeted estimator usable to yield an improved estimator of a particular feature relative to an estimate of the feature that would be provided via an initial estimator provided by the initial estimator module. - View Dependent Claims (15, 16)
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17. Software encoded in one or more tangible media for non-transitory computer-readable medium execution by the one or more processors and when executed operable to:
- determine data;
determine a target feature pertaining to the data;
determine an initial estimator descriptive of a first distribution of the data; and
selectively modify the initial estimator based on the target feature to determine a modified estimator, the modified estimator providing a second distribution of the data, wherein selectively modifying includes iteratively updating the modified estimator by using a previously determined modified estimator to provide the initial estimator for a subsequent iteration.
- determine data;
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18. A method comprising:
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obtaining a dataset; and mapping a prior probability distribution of a target feature to a posterior distribution of the target feature using an estimator of a probability distribution of the dataset and a stretching function. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
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Specification