Abstract
This chapter includes an introduction to the base matrices we will use to fit the Bayesian Belief Networks in Chapters 7–9. It provides information on the model fitting process, for the base Node A; and the synthetic node creation for Nodes B, C, and D, using frequency counts and likelihood probabilities.
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Notes
- 1.
Chapter 5 was a rewrite of Grover, 2013.
- 2.
Joint nodes are those that have common elements, and disjoint nodes have no common elements.
- 3.
We used the online combinations calculator @ http://www.mathsisfun.com/combinatorics/combinations-permutations-calculator.html. We calculated the number of paths for each BBN using Eq. (3.4) and referenced the values of n and r.
- 4.
Note: * Denotes randomly omitted paths.
- 5.
We counted and populated these data, from the random experiment for this manual.
- 6.
These data are counted from the random experiment conducted to populate the data for this manual.
- 7.
The strikethrough represent a disjoint node.
- 8.
Strikethroughs represent disjoint nodes.
- 9.
Strikethroughs represent disjoint nodes.
References
Combinations and Permutations Calculator. (n.d.). Retrieved November 06, 2016, from http://www.mathsisfun.com/combinatorics/combinations-permutations-calculator.html.
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© 2016 Springer International Publishing AG
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Grover, J. (2016). Base Matrices. In: The Manual of Strategic Economic Decision Making. Springer, Cham. https://doi.org/10.1007/978-3-319-48414-3_6
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DOI: https://doi.org/10.1007/978-3-319-48414-3_6
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-48414-3
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