Grobner bases and factorisation in discrete probability and Bayes
UNSPECIFIED (2001) Grobner bases and factorisation in discrete probability and Bayes. In: Workshop on Symbolic Computation in Statistics, MONTREAL, CANADA, SEP, 1997. Published in: STATISTICS AND COMPUTING, 11 (1). pp. 37-46.Full text not available from this repository.
Grobner bases, elimination theory and factorization may be used to perform calculations in elementary discrete probability and more complex areas such as Bayesian networks (influence diagrams). The paper covers the application of computational algebraic geometry to probability theory. The application to the Boolean algebra of events is straightforward (and essentially known). The extension into the probability superstructure is via the polynomial interpolation of densities and log densities and this is used naturally in the Bayesian application.
|Item Type:||Conference Item (UNSPECIFIED)|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Q Science > QA Mathematics
|Journal or Publication Title:||STATISTICS AND COMPUTING|
|Publisher:||KLUWER ACADEMIC PUBL|
|Official Date:||January 2001|
|Number of Pages:||10|
|Page Range:||pp. 37-46|
|Title of Event:||Workshop on Symbolic Computation in Statistics|
|Location of Event:||MONTREAL, CANADA|
|Date(s) of Event:||SEP, 1997|
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