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Abstract: Statistical inference procedures are considered when less complete prior information is available than usually considered.
Abstract-Statistical inference procedures are considered when less complete prior information is available than usually considered. For the.
We show how a generalization of Gauss' inequality can be used to determine the relevant parameter subset.
Mar 13, 2022 · This paper ties the two frameworks together by formally treating those cases where only partial prior information is available using the theory of imprecise ...
Statistical inference with partial prior information based on a Gauss-type inequality · A method for assessing the worth of prior knowledge about the measurand.
Statistical inference procedures are considered when less complete prior information is available than usually considered. For the purposes of this paper, ...
Partial prior information on the marginal distribution of an observable random variable is considered. When this information is incorporated into the ...
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Sep 23, 2023 · This series of papers rigorously develops a new and very general inferential model (IM) framework for imprecise-probabilistic statistical inference that is ...
This paper considers statistical inference in contexts where only incomplete prior information is available. We develop a practical construction of a ...
[PDF] Bayesian Inference Under Partial Prior Information - CiteSeerX
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Partial prior information on the marginal distribution of an observable random variable is considered. When this information is incorporated into the ...