Description Usage Arguments Details Value Examples
Mutual Information test of independence. Mutual Information are generic dependence measures in Banach spaces.
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x |
A numeric vector, matrix, data.frame or |
y |
A numeric vector, matrix, data.frame or |
k |
Order of neighborhood to be used in the kNN method. |
distance |
Bool flag for considering |
num.permutations |
The number of permutation replications.
If |
seed |
The random seed. Default: |
If two samples are passed to arguments x
and y
, the sample sizes
(i.e. number of rows of the matrix or length of the vector) must agree.
Moreover, data being passed to x
and y
must not contain missing or infinite values.
mi.test
utilizes the Mutual Information statistics (see mi
)
to measure dependence and derive a p-value via replicating the random permutation num.permutations
times.
If num.permutations > 0
, mi.test
returns a htest
class object containing the following components:
|
Mutual Information statistic. |
|
The p-value for the test. |
|
Permutation replications of the test statistic. |
|
Sample size. |
|
A character string describes the alternative hypothesis. |
|
A character string indicates what type of test was performed. |
|
Description of data. |
If num.permutations = 0
, mi.test
returns a statistic value.
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