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Modal Cluster in Bivariate

Anybody have any notes on what Modal Cluster in Bivariate is doing?  It's an option under the Nonpar Density LRT Menu.  The doc's have 1 sentence on page 146 and nothing in the statistical details.  

 

Thanks!

 

M 

Re: Modal Cluster in Bivariate

Here's what tech support came back with:

"Modal clustering is just finding peaks in the density and collecting all the points that are on the downhill of the gradient to that peak. SAS Proc MODECLUS does this, though it is in more dimensions, not just two, and it uses near-neighbor estimates rather than kernel estimates. The default kernel is chosen according to the Bowman-Foster recommendation: .5*stdDev*n^(1/6). [Link to paper]"

There's a link to the paper included - it's open content, so anyone can download if they want to go really deep into the weeds.  

 

 

Re: Modal Cluster in Bivariate

I didn’t know this cool feature, but now I’ve played with it since your post. It seems it has been available in JMP a long time.

The modal clustering classifies data points into clusters through the kernel density estimation. Using Big Class as an example I ran Fit Height by Weight and then select the Nonpar Density and Modal Clustering. It automatically saves a Cluster column to the data table. In this example there are 14 clusters assigned based on the contours drawn ( i.e., there are 14 peaks in the bivariate density). To makes sense of it I ran Distribution and GB, and placed them in a dashboard.

To illustrate the modal clustering, I allow the quadratic curve in GB automatically updating with the Cluster selection but keep the curve in the Bivariare fixed to the whole data set. As you can see, overall there is a strong upward curvature between Height and Weight, but for Cluster 9 it’s downward. You can also see where these data points are.