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Mathematics
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Mathematics
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Mathematics
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https://dx.doi.org/10.48550/ar...
Article . 2019
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Diffeological Statistical Models, the Fisher Metric and Probabilistic Mappings

Authors: Hông Vân Lê;

Diffeological Statistical Models, the Fisher Metric and Probabilistic Mappings

Abstract

We introduce the notion of a C k -diffeological statistical model, which allows us to apply the theory of diffeological spaces to (possibly singular) statistical models. In particular, we introduce a class of almost 2-integrable C k -diffeological statistical models that encompasses all known statistical models for which the Fisher metric is defined. This class contains a statistical model which does not appear in the Ay–Jost–Lê–Schwachhöfer theory of parametrized measure models. Then, we show that, for any positive integer k , the class of almost 2-integrable C k -diffeological statistical models is preserved under probabilistic mappings. Furthermore, the monotonicity theorem for the Fisher metric also holds for this class. As a consequence, the Fisher metric on an almost 2-integrable C k -diffeological statistical model P ⊂ P ( X ) is preserved under any probabilistic mapping T : X ⇝ Y that is sufficient w.r.t. P. Finally, we extend the Cramér–Rao inequality to the class of 2-integrable C k -diffeological statistical models.

Country
Czech Republic
Keywords

probabilistic mapping, statistical model, Probability (math.PR), Mathematics - Statistics Theory, Statistics Theory (math.ST), 62B-05, 62F-10, diffeology, Cramér-Rao inequality, QA1-939, FOS: Mathematics, the Fisher metric, the fisher metric, Mathematics, Mathematics - Probability, cramér-rao inequality

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
Green
gold
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