Local probability distributions
Methods for accessing or changing the local probability distributions and for accessing the local prior and posterior distributions
prob(x,df,...) ## S3 method for class 'node' prob(x,df,nw,...) ## S3 method for class 'network' prob(x,df,...) localprob(nw) localprob(nw,name) <- value localprior(node) localposterior(node)
x |
an object of class |
df |
a data frame, where the columns define the variables. A
continuous variable should have type |
nw |
an object of class |
node |
an object of class |
name |
a string, which gives the node name. |
... |
additional arguments for specific methods. |
value |
If the node is continuous, this is a numeric vector with the conditional variance and the conditional regression coefficients arising from a regression on the continuous parents, using data. If the node has discrete parents, it is a matrix with a row for each configuration of the discrete parents. If the node is discrete, it is a multiway array which gives the conditional probability distribution for each configuration of the discrete parents. |
The prob methods add local
probability distributions to
each node. If the node is continuous, this is a
numeric vector with
the conditional variance and the conditional regression coefficients
arising from a regression on the continuous parents, using data. If
the node has discrete parents, prob is a matrix with a row
for each configuration of the discrete parents. If the node is
discrete, prob is a multiway array which gives the conditional
probability distribution for each configuration of the discrete
parents. The generated prob can be replaced to match the prior
information available.
localprob returns the probability distribution
for each node in the network.
In a learned network, the local prior and posterior can be accessed
for each node using localprior and localposterior.
Susanne Gammelgaard Bottcher,
Claus Dethlefsen rpackage.deal@gmail.com.
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