performSampling: Perform sampling
In mickash/Adaptive-Bayesian-Networks: Adaptive Bayesian Networks.
Description
Usage
Arguments
Value
View source: R/infer_bayesnet.R
Description
Perform sampling
Usage
1
performSampling(algo, net, evidence, num, algoSpecific = NULL)
Arguments
algo
A string specifying a valid algorithm.
"IS" = Importance sampling.
"BS" = Backwards sampling
"SU" = Selected uniform sampling
"MC" = MCMC sampling
net
the network
evidence
vector of integers specifying known values of nodes. This
can include NA values for unknown variables.
num
integer specifying the number of samples to used in inference
algoSpecific
An algorithm specific object:
For importance sampling, this should specify "nat" or "aux" depending on
whether auxiliary variables should be sampled, or only the natural variables.
Value
The generated samples
mickash/Adaptive-Bayesian-Networks documentation built on Nov. 14, 2019, 12:14 a.m.
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Description Usage Arguments Value
View source: R/infer_bayesnet.R
Description
Perform sampling
Usage
1 | performSampling(algo, net, evidence, num, algoSpecific = NULL)
|
Arguments
algo |
A string specifying a valid algorithm. "IS" = Importance sampling. "BS" = Backwards sampling "SU" = Selected uniform sampling "MC" = MCMC sampling |
net |
the network |
evidence |
vector of integers specifying known values of nodes. This can include NA values for unknown variables. |
num |
integer specifying the number of samples to used in inference |
algoSpecific |
An algorithm specific object: For importance sampling, this should specify "nat" or "aux" depending on whether auxiliary variables should be sampled, or only the natural variables. |
Value
The generated samples
R Package Documentation
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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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