Loss: Compute loss of the network on the timeseries.
In davidkwca/inferTPBN: Infer Threshold PBNs from Timeseries Data.
Description
Usage
Arguments
Value
See Also
Examples
Description
This computes the complete loss of the network on a timeseries.
If desired, the prior penalty can be included.
Usage
1
Arguments
ts.multi
List of timeseries.
net
A PBN.
prior
If TRUE, loss for the prior is included. Defaults to TRUE.
Value
A float.
See Also
LossGeneTotal LossGeneTimeseries LossPriorGene
Examples
1
2
3
net <- createNetwork(inputProbabilities=1, 5, 2, "homogeneous")
ts.multi <- simulateNetwork(net, 10, 50) # Creates 50 timeseries à 10 points
loss <- Loss(ts.multi, net)
davidkwca/inferTPBN documentation built on May 9, 2019, 12:53 p.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.
Description Usage Arguments Value See Also Examples
Description
This computes the complete loss of the network on a timeseries. If desired, the prior penalty can be included.
Usage
1 |
Arguments
ts.multi |
List of timeseries. |
net |
A PBN. |
prior |
If TRUE, loss for the prior is included. Defaults to TRUE. |
Value
A float.
See Also
LossGeneTotal LossGeneTimeseries LossPriorGene
Examples
1 2 3 | net <- createNetwork(inputProbabilities=1, 5, 2, "homogeneous")
ts.multi <- simulateNetwork(net, 10, 50) # Creates 50 timeseries à 10 points
loss <- Loss(ts.multi, net)
|
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.