testing for bimodal and for dip in between modes in R
Testing for bimodality is rather testing for unimodality. Hartigan and Hartigan (1985) presented the Dip-Test which is implemented in the R package DipTest with a much better approximation of the test distribution. If the test statistic is too high unimodality is rejected. To estimate the dip point you could choose among several possibilities: (1) A very easy method is to use the kmeans function for a kmeans cluster and use the point in the middle of the connecting line between the kmeans cluster centers. (2) You could estimate a finite mixture distribution and take the middle of the connecting line of the modes. Best Simon
On 24 Nov 2013, at 20:41, Felix Breden <breden at sfu.ca> wrote:
Hi I have distributions that are typically bimodal (see attached .pdf), and I would like to test for bimodality, and then estimate the point between the two modes, the dip in the distributions. any help would be greatly appreciated. thanks felix <m66.junction.aln.pairwise.histogram.pdf>______________________________________________ R-help at r-project.org mailing list
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