Diffeological statistical models, the Fisher metric and probabilistic mappings
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985840%3A_____%2F20%3A00521519" target="_blank" >RIV/67985840:_____/20:00521519 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.3390/math8020167" target="_blank" >https://doi.org/10.3390/math8020167</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/math8020167" target="_blank" >10.3390/math8020167</a>
Alternative languages
Result language
angličtina
Original language name
Diffeological statistical models, the Fisher metric and probabilistic mappings
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10101 - Pure mathematics
Result continuities
Project
<a href="/en/project/GC18-01953J" target="_blank" >GC18-01953J: Geometric methods in statistical learning theory and applications</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Mathematics
ISSN
2227-7390
e-ISSN
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Volume of the periodical
8
Issue of the periodical within the volume
2
Country of publishing house
CH - SWITZERLAND
Number of pages
13
Pages from-to
167
UT code for WoS article
000519234000022
EID of the result in the Scopus database
2-s2.0-85080125263