fpc: diptest.multi – R documentation

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diptest.multi

Diptest for discriminant coordinate projection

Description

Diptest (Hartigan and Hartigan, 1985, see dip) for data projected in discriminant coordinate separating optimally two class means (see discrcoord) as suggested by Tantrum, Murua and Stuetzle (2003).

Usage

diptest.multi(xdata,class,pvalue="uniform",M=100)

Arguments

`xdata`	matrix. Potentially multidimensional dataset.
`class`	vector of integers giving class numbers for observations.
`pvalue`	`"uniform"` or `"tantrum"`. Defines whether the p-value is computed from a uniform null model as suggested in Hartigan and Hartigan (1985, using `dip.test`) or as suggested in Tantrum et al. (2003, using `dipp.tantrum`).
`M`	integer. Number of artificial datasets generated in order to estimate the p-value if `pvalue="tantrum"`.

Value

The resulting p-value.

Author(s)

Christian Hennig christian.hennig@unibo.it https://www.unibo.it/sitoweb/christian.hennig/en/

References

J. A. Hartigan and P. M. Hartigan (1985) The Dip Test of Unimodality, Annals of Statistics, 13, 70-84.

Tantrum, J., Murua, A. and Stuetzle, W. (2003) Assessment and Pruning of Hierarchical Model Based Clustering, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, Washington, D.C., 197-205.

Examples

require(diptest)
  x <- cbind(runif(100),runif(100))
  partition <- 1+(x[,1]<0.5)
  d1 <- diptest.multi(x,partition)
  d2 <- diptest.multi(x,partition,pvalue="tantrum",M=10)

fpc

Flexible Procedures for Clustering

v2.2-9

GPL

Authors

Christian Hennig <christian.hennig@unibo.it>

Initial release

2020-12-06