Information geometry and sufficient statistics

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985840%3A_____%2F15%3A00444389" target="_blank" >RIV/67985840:_____/15:00444389 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s00440-014-0574-8" target="_blank" >http://dx.doi.org/10.1007/s00440-014-0574-8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00440-014-0574-8" target="_blank" >10.1007/s00440-014-0574-8</a>

Result language
angličtina
Original language name
Information geometry and sufficient statistics
Original language description
Information geometry provides a geometric approach to families of statistical models. The key geometric structures are the Fisher quadratic form and the Amari?Chentsov tensor. In statistics, the notion of sufficient statistic expresses the criterion forpassing from one model to another without loss of information. This leads to the question how the geometric structures behave under such sufficient statistics. While this is well studied in the finite sample size case, in the infinite case, we encountertechnical problems concerning the appropriate topologies. Here, we introduce notions of parametrized measure models and tensor fields on them that exhibit the right behavior under statistical transformation.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BA - General mathematics
OECD FORD branch
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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