How to add a new distribution formula to the distribution analysis

[#1]

Hi, 

I'm working with measurement data that should follow a specific distribution.

My goal is to create a Folded Normal and a Rayleigh to compare along with other distributions already programmed by default in JMP in order to see if my data follows the expected one.

Here I fit all distributions with my data and look if the normal distribution fits the best according to the AICc. I would like to do the same with a Folded Normal and a Rayleigh law.

Here is the corresponding code :

	DistributionChart = Distribution(//Creation of the distribution chart
		Continuous Distribution(
			Column( dTempoClean:Ecart ),
			Quantiles( 0 ),
			Normal Quantile Plot( 1 ),
			Process Capability( 0 )	
		),
		Histograms Only
		SendToReport(
			Dispatch( {"Ecart mesurée"}, "1", ScaleBox,//Deviation data is studied
				{Add Ref Line(lst, "Solid", "Blue", "Tol. Inf.", 1 ),
				Add Ref Line(ust, "Solid", "Blue", "Tol. sup.", 1 ),
				Add Ref Line(0, "Solid", "Blue", "Objectif", 1 )}
			),
			Dispatch( {"Ecart mesurée"}, "", Picture Box( 4 ),
				{Set Summary Behavior( "Collapse" )}
			)
		)
	);

	DistributionChart << Fit All;//Fit all default distributions 
	scb = Report(DistributionChart)[Outline Box("Compare Distributions"), Table Box(1), NumberColBox("AICc")];//Get AICc value
	scb1 = Report(DistributionChart)[Outline Box("Compare Distributions"), Table Box(1), StringColBox(1)];//Get best distribution name
	k=1;
	while (scb[k]==".",k++)
	bestdist = scb1[k];

How can I add a Folded Normal and a Rayleigh distribution to the Fit All while getting all the corresponding statistical data (Mean, Standard Deviation, Cp, Cpk...) ?

Thank you very much for your help ! 

[#2]

The folded normal and Rayleigh, are special cases of the Weibull distribution. Unless someone else knows a special trick, it is not possible to add additional distribution models to the menu.