Message-ID: <2D315B7B-29AB-4BE5-B067-2116ADCE41E8@uni-bonn.de>
Date: 2013-11-25T11:31:22Z
From: Simon Zehnder
Subject: testing for bimodal and for dip in between modes in R
In-Reply-To: <1314763945.410655617.1385322067823.JavaMail.root@jaguar7.sfu.ca>
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>______________________________________________
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