htt_control | R Documentation |
Various parameters that control aspects of the HTT
function.
htt_control(teststat = c("energy0", "energy1"),
testtype = c("permutation", "fastpermutation"),
alpha = 1, pt = 0.05, minsplit = 30,
minbucket = round(minsplit/3),
R = 199, nmin = 1000)
teststat |
a character specifying the type of the test statistic to be applied.
It can be |
testtype |
a character specifying how to compute the distribution of the test statistic.
It can be |
alpha |
the exponent on Euclidean distance in (0,2] (for regression tree).
Default is |
pt |
the p-value of the permutation test must be less than in order to implement a split.
If |
minsplit |
the minimum number of observations in a node
in order to be considered for splitting.
Default is |
minbucket |
the minimum number of observations in a terminal node.
Default is |
R |
the number of permutation replications are used to simulated
the distribution of the test statistic.
Default is |
nmin |
the minimum number of observations in a node that does not require
the permutation test (for |
The arguments teststat
, testtype
and pt
determine
the hypothesis testing of each split.
The argument R
is the number of permutations to be used.
For the dataset with more than 2000 observations, testtype = "fastpermutation"
will be useful to save time.
A list containing the options.
HTT
, htt.object
## choose the teststat as "energy1"
htt_control(teststat = "energy1")
## choose the p-value 0.01
htt_control(pt = 0.01)
## choose the alpha to 0.5
htt_control(alpha = 0.5)
## change the minimum number of observations in a terminal node
htt_control(minbucket = 7)
## reduce the number of permutation replications to save time
htt_control(R = 99)
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