dbn_generator: Generates a random dynamic Bayesian network
In ramidst: An Interface to the AMIDST Toolbox for Data Stream Processing
Description
Usage
Arguments
Value
Examples
Description
Generates a random dynamic Bayesian network
Usage
1
dbn_generator(n_c_vars, n_d_vars, n_s)
Arguments
n_c_vars
the number of Gaussian variables
n_d_vars
the number of discrete variables
n_s
the number of states of the discrete variables
Value
a Java object of class DynamicBayesianNetwork
Examples
1
2
d <- dbn_generator(3,2,2)
print_amidst_bn(d)
ramidst documentation built on May 30, 2017, 5:27 a.m.
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Description Usage Arguments Value Examples
Description
Generates a random dynamic Bayesian network
Usage
1 | dbn_generator(n_c_vars, n_d_vars, n_s)
|
Arguments
n_c_vars |
the number of Gaussian variables |
n_d_vars |
the number of discrete variables |
n_s |
the number of states of the discrete variables |
Value
a Java object of class DynamicBayesianNetwork
Examples
1 2 | d <- dbn_generator(3,2,2)
print_amidst_bn(d)
|
ramidst documentation built on May 30, 2017, 5:27 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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