Description Usage Arguments Details Value Note Author(s) See Also Examples
Assign, extract or compute various quantities of interest from an object
of class bn.fit
, bn.fit.dnode
, bn.fit.gnode
or
bn.fit.onode
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | ## methods available for "bn.fit"
## S3 method for class 'bn.fit'
fitted(object, ...)
## S3 method for class 'bn.fit'
coef(object, ...)
## S3 method for class 'bn.fit'
residuals(object, ...)
## S3 method for class 'bn.fit'
predict(object, node, data, ..., debug = FALSE)
## S3 method for class 'bn.fit'
logLik(object, data, nodes, by.sample = FALSE, ...)
## S3 method for class 'bn.fit'
AIC(object, data, ..., k = 1)
## S3 method for class 'bn.fit'
BIC(object, data, ...)
## methods available for "bn.fit.dnode"
## S3 method for class 'bn.fit.dnode'
coef(object, ...)
## S3 method for class 'bn.fit.dnode'
predict(object, data, ..., debug = FALSE)
## methods available for "bn.fit.onode"
## S3 method for class 'bn.fit.onode'
coef(object, ...)
## S3 method for class 'bn.fit.onode'
predict(object, data, ..., debug = FALSE)
## methods available for "bn.fit.gnode"
## S3 method for class 'bn.fit.gnode'
fitted(object, ...)
## S3 method for class 'bn.fit.gnode'
coef(object, ...)
## S3 method for class 'bn.fit.gnode'
residuals(object, ...)
## S3 method for class 'bn.fit.gnode'
predict(object, data, ..., debug = FALSE)
|
object |
an object of class |
node |
a character string, the label of a node. |
nodes |
a vector of character strings, the label of a nodes whose loglikelihood components are to be computed. |
data |
a data frame containing the variables in the model. |
... |
additional arguments (currently ignored). |
k |
a numeric value, the penalty per parameter to be used; the
default |
by.sample |
a boolean value. If |
debug |
a boolean value. If |
coef
(and its alias coefficients
) extracts model
coefficients (which are conditional probabilities in discrete
networks and linear regression coefficients in Gaussian networks).
residuals
(and its alias resid
) extracts model
residuals and fitted
(and its alias fitted.values
)
extracts fitted values from fitted Gaussian networks.
If the bn.fit
object does not include the residuals or the
fitted values (for the nodes of interest, in the case of
bn.fit.gnode
objects), both functions return NULL
.
predict
returns the predicted values for node
for
the data specified by data
.
predict
returns a numeric vector (for Gaussian networks) or a factor
(for discrete networks).
logLik
returns a numeric vector or a single numeric value, depending
on the value of by.sample
. AIC
and BIC
always return
a single numeric value.
All the other functions return a list with an element for each node in
the network (if object
has class bn.fit
) or a numeric
vector (if object
has class bn.fit.dnode
or bn.fit.gnode
).
Ties in prediction are broken using Bayesian tie breaking, i.e. sampling at random from the tied values. Therefore, setting the random seed is required to get reproducible results.
Marco Scutari
1 2 3 4 5 6 7 8 9 10 11 | data(gaussian.test)
res = hc(gaussian.test)
fitted = bn.fit(res, gaussian.test)
coefficients(fitted)
coefficients(fitted$C)
str(residuals(fitted))
data(learning.test)
res2 = hc(learning.test)
fitted2 = bn.fit(res2, learning.test)
coefficients(fitted2$E)
|
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