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Autor principal: Cella, Leonardo
Formato: Preprint
Publicado: 2024
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Acceso en línea:https://arxiv.org/abs/2405.07173
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author Cella, Leonardo
author_facet Cella, Leonardo
contents Inferential models (IMs) represent a novel possibilistic approach for achieving provably valid statistical inference. This paper introduces a general framework for fusing independent IMs in a "black-box" manner, requiring no knowledge of the original IMs construction details. The underlying logic of this framework mirrors that of the IMs approach. First, a fusing function for the initial IMs' possibility contours is selected. Given the possible lack of guarantee regarding the calibration of this function for valid inferences, a "validification" step is performed. Subsequently, a straightforward normalization step is executed to ensure that the final output conforms to a possibility contour.
format Preprint
id arxiv_https___arxiv_org_abs_2405_07173
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Fusing independent inferential models in a black-box manner
Cella, Leonardo
Statistics Theory
Inferential models (IMs) represent a novel possibilistic approach for achieving provably valid statistical inference. This paper introduces a general framework for fusing independent IMs in a "black-box" manner, requiring no knowledge of the original IMs construction details. The underlying logic of this framework mirrors that of the IMs approach. First, a fusing function for the initial IMs' possibility contours is selected. Given the possible lack of guarantee regarding the calibration of this function for valid inferences, a "validification" step is performed. Subsequently, a straightforward normalization step is executed to ensure that the final output conforms to a possibility contour.
title Fusing independent inferential models in a black-box manner
topic Statistics Theory
url https://arxiv.org/abs/2405.07173