Nonparametric estimations and the diffeological Fisher metric
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985840%3A_____%2F21%3A00544050" target="_blank" >RIV/67985840:_____/21:00544050 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-77957-3_7" target="_blank" >http://dx.doi.org/10.1007/978-3-030-77957-3_7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-77957-3_7" target="_blank" >10.1007/978-3-030-77957-3_7</a>
Alternative languages
Result language
angličtina
Original language name
Nonparametric estimations and the diffeological Fisher metric
Original language description
In this paper, first, we survey the concept of diffeological Fisher metric and its naturality, using functorial language of probabilistic morphisms, and slightly extending Lê’s theory in [Le2020] to include weakly Ck-diffeological statistical models. Then we introduce the resulting notions of the diffeological Fisher distance, the diffeological Hausdorff–Jeffrey measure and explain their role in classical and Bayesian nonparametric estimation problems in statistics.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10101 - Pure mathematics
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Geometric Structures of Statistical Physics, Information Geometry, and Learning
ISBN
978-3-030-77956-6
ISSN
2194-1009
e-ISSN
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Number of pages
19
Pages from-to
120-138
Publisher name
Springer
Place of publication
Cham
Event location
Les Houches
Event date
Jul 27, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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