| Title:
|
Discriminating between causal structures in Bayesian Networks given partial observations (English) |
| Author:
|
Moritz, Philipp |
| Author:
|
Reichardt, Jörg |
| Author:
|
Ay, Nihat |
| Language:
|
English |
| Journal:
|
Kybernetika |
| ISSN:
|
0023-5954 (print) |
| ISSN:
|
1805-949X (online) |
| Volume:
|
50 |
| Issue:
|
2 |
| Year:
|
2014 |
| Pages:
|
284-295 |
| Summary lang:
|
English |
| . |
| Category:
|
math |
| . |
| Summary:
|
Given a fixed dependency graph $G$ that describes a Bayesian network of binary variables $X_1, \dots, X_n$, our main result is a tight bound on the mutual information $I_c(Y_1, \dots, Y_k) = \sum_{j=1}^k H(Y_j)/c - H(Y_1, \dots, Y_k)$ of an observed subset $Y_1, \dots, Y_k$ of the variables $X_1, \dots, X_n$. Our bound depends on certain quantities that can be computed from the connective structure of the nodes in $G$. Thus it allows to discriminate between different dependency graphs for a probability distribution, as we show from numerical experiments. (English) |
| Keyword:
|
Bayesian networks |
| Keyword:
|
causal Markov condition |
| Keyword:
|
information theory |
| Keyword:
|
information inequalities |
| Keyword:
|
common ancestors |
| Keyword:
|
causal inference |
| MSC:
|
60A08 |
| MSC:
|
62-09 |
| MSC:
|
62B09 |
| MSC:
|
62H99 |
| idZBL:
|
Zbl 06325225 |
| idMR:
|
MR3216995 |
| DOI:
|
10.14736/kyb-2014-2-0284 |
| . |
| Date available:
|
2014-06-06T14:49:16Z |
| Last updated:
|
2016-01-03 |
| Stable URL:
|
http://hdl.handle.net/10338.dmlcz/143794 |
| . |
| Reference:
|
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| . |
