utest: U test
In gcybis/Uclust: Clustering and Classification Inference with U-Statistics

Description Usage Arguments Details Value See Also Examples

Test for the separation of two groups. The null hypothesis states that the groups are homogeneous and the alternative hypothesis states that they are separate.

1	utest(group_id, md = NULL, data = NULL, numB = 1000)

`group_id`	A vector of 0s and 1s indicating to which group the samples belong. Must be in the same order as data or md.
`md`	Matrix of distances between all data points.
`data`	Data matrix. Each row represents an observation.
`numB`	Number of resampling iterations.

Either data or md should be provided. If data are entered directly, Bn will be computed considering the squared Euclidean distance, which is compatible with is_homo, uclust and uhclust.

For more details see Cybis, Gabriela B., Marcio Valk, and Sílvia RC Lopes. "Clustering and classification problems in genetics through U-statistics." Journal of Statistical Computation and Simulation 88.10 (2018)

Returns a list with the following elements:

Bn: Test Statistic
Pvalue: Replication based p-value
Replication: Number of replications used to compute p-value

bn,is_homo

# Simulate a dataset with two separate groups, the first 5 rows have mean 0 and
# the last 5 rows have mean 5.
data <- matrix(c(rnorm(75, 0), rnorm(75, 5)), nrow = 10, byrow=TRUE)

# U test for mixed up groups
utest(group_id=c(1,0,1,0,1,0,1,0,1,0), data=data, numB=3000)
# U test for correct group definitions
utest(group_id=c(1,1,1,1,1,0,0,0,0,0), data=data, numB=3000)