Description Usage Arguments Value Author(s) See Also Examples
Various parameters that control aspects for tvcm
.
1 2 3 4 5 6 7 8 9 10  tvcm_control(minsize = 30, mindev = ifelse(sctest, 0.0, 2.0),
sctest = FALSE, alpha = 0.05, bonferroni = TRUE,
trim = 0.1, estfun.args = list(), nimpute = 5,
maxnomsplit = 5, maxordsplit = 9, maxnumsplit = 9,
maxstep = 1e3, maxwidth = Inf, maxdepth = Inf,
lossfun = neglogLik2, ooblossfun = NULL, fast = TRUE,
cp = 0.0, dfpar = 0.0, dfsplit = 1.0,
cv = !sctest, folds = folds_control("kfold", 5),
prune = cv, papply = mclapply, papply.args = list(),
center = fast, seed = NULL, verbose = FALSE, ...)

alpha, bonferroni, trim, estfun.args, nimpute 
See

mindev, cv, folds, prune, center 
See

minsize 
numeric (vector). The minimum sum of weights in terminal nodes. 
sctest 
logical scalar. Defines whether coefficient constancy tests should be used for the variable and node selection in each iteration. 
maxnomsplit 
integer. For nominal partitioning variables with
more the 
maxordsplit 
integer. The maximum number of splits of ordered partitioning variables to be evaluated. 
maxnumsplit 
integer. The maximum number of splits of numeric partitioning variables to be evaluated. 
maxstep 
integer. The maximum number of iterations i.e. number of splits to be processed. 
maxwidth 
integer (vector). The maximum width of the partition(s). 
maxdepth 
integer (vector). The maximum depth of the partition(s). 
lossfun 
a function to extract the training error, typically
minus two times the negative log likelihood of the fitted model (see

ooblossfun 
a loss function that defines how to compute the
validation error during crossvalidation. The function will be
assigned to the 
fast 
logical scalar. Whether the approximative model should be
used to search for the next split. The approximative search model
uses only the observations of the node to split and incorporates the
fitted values of the current model as offsets. Therewith the
estimation is reduces to the coefficients of the added split. If

cp 
numeric scalar. The penalty to be multiplied with the
complexity of the model during partitioning. The complexity of the
model is defined as the number of coefficients times 
dfpar 
numeric scalar. The degree of freedom per model
coefficient. Is used to compute the complexity of the model, see

dfsplit 
a numeric scalar. The degree of freedom per split. Is
used to compute the complexity of the model, see 
papply 
(parallel) apply function, defaults to

papply.args 
a list of arguments to be passed to 
seed 
an integer specifying which seed should be set at the beginning. 
verbose 
logical. Should information about the fitting process be printed to the screen? 
... 
further, undocumented arguments to be passed. 
A list of class tvcm_control
containing
the control parameters for tvcm
.
Reto Buergin
tvcolmm_control
,
tvcglm_control
, tvcm
,
fvcm
1  tvcm_control(minsize = 100)

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