Title
Invariant Geometric Structures On Statistical Models
Abstract
We review the notion of parametrized measure models and tensor fields on them, which encompasses all statistical models considered by Chentsov [6], Amari [3] and Pistone-Sempi [10]. We give a complete description of n-tensor fields that are invariant under sufficient statistics. In the cases n = 2 and n = 3, the only such tensors are the Fisher metric and the Amari-Chentsov tensor. While this has been shown by Chentsov [7] and Campbell [5] in the case of finite measure spaces, our approach allows to generalize these results to the cases of infinite sample spaces and arbitrary n. Furthermore, we give a generalisation of the monotonicity theorem and discuss its consequences.
Year
DOI
Venue
2015
10.1007/978-3-319-25040-3_17
GEOMETRIC SCIENCE OF INFORMATION, GSI 2015
Field
DocType
Volume
Discrete mathematics,Monotonic function,Tensor,Tensor field,Banach space,Invariant (mathematics),Sample space,Sufficient statistic,Mathematics,Logarithmic derivative
Conference
9389
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Lorenz Schwachhöfer100.34
Nihat Ay235847.47
Jürgen Jost39512.39
Hông Vân Lê400.68