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  • JMP Security Notice: CVE-2026-109618 and CVE-2026-109619

    JMP promptly initiated a review of its products, services, and relevant infrastructure for exposure to CVE-2026-109618 and CVE-2026-109619.

    Our assessment of JMP products has not identified exposure to these vulnerabilities. Where remediation was required within supporting environments, appropriate security updates and controls have been applied and validated.

    We have identified no evidence of successful exploitation or unauthorized access to JMP systems or customer information associated with these vulnerabilities.

    JMP continues to monitor the issue and relevant vendor guidance. No action is required by JMP customers at this time.

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JMP Wish List

We want to hear your ideas for improving JMP. Share them here.
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More distributions to handle data sets with zero's or negative values

What inspired this wish list request? 

I analyze a lot of data that is a deviation from nominal and thus has values at zero or negative values.  If the data is skewed there are much more limited Distibution fitting options in both the Distribution platform and the Capability platform (and no options in Process screener!).

 

 

What is the improvement you would like to see?

I would like to see additional distributions such as largest and smallest extreme values, 3 parameter Weibull/Gamma/Exponential/Lognormal, and zero inflated distributions as asked for here:

Add Zero Inflated distributions to Distribution Platform - JMP User Community

in the Distribution Platform, Capability Platform, and the Process Screening Platform.

 

Why is this idea important?

Since a proper capability analysis requires the need for a well fitting distribution, having a large number of options is key for user success.  As such, currently any skewed data set that includes values at 0 or less can lead to poor capability analysis due to more limited fitting options that >0 data sets.