Description Usage Arguments Details Value See Also Examples
Trees based maximumlikelihood estimation of parameters for a circular response employing a von Mises distribution.
1 2 
formula 
A symbolic description of the model to be fit. This
should be of type 
data 
An optional data frame containing the variables in the model. 
start 
Starting values of distribution parameters used in the optimization. Currently, not supported. 
subset 
An optional vector specifying a subset of observations to be used for fitting. Currently, not supported. 
na.action 
A function which indicates what should happen when the data
contain 
weights 
Optional numeric vector of case weights. 
offset 
Optional numeric vector with a priori known component to be included in the linear predictor for the location. Currently, not supported. 
control 
Control arguments passed to 
fit_control 
A list of control parameters passed to

... 
Arguments to be used to form the default 
Regression trees employing a von Mises distribution is an application of modelbased recursive partitioning
and unbiased recursive partitioning based on the implementation in mob
.
An object of S3 class circtree
inheriting from class modelparty
or constparty
.
1 2 3 4 5  sdat < circtree_simulate()
m1.circtree < circtree(y ~ x1 + x2, data = sdat)
#plot(m1.circtree, tp_args = list(kernel_density = TRUE))
plot(m1.circtree)

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