Re: weibull plot on weibull scaled paper

*To*: mathgroup at smc.vnet.net*Subject*: [mg116753] Re: weibull plot on weibull scaled paper*From*: DrMajorBob <btreat1 at austin.rr.com>*Date*: Sat, 26 Feb 2011 06:07:07 -0500 (EST)

Technical support replied to me saying, in part: "It does appear that there is issue with Weibull distribution estimation code. This issue is known to our developers and a fix will be made available to the users with the future update to Mathematica. I have forwarded an incident report to our developers with the information you provided along with your name and contact information so that you can be contacted once the issue is resolved. In the meantime, the plot generated by the ProbabilityScalePlot can still be used." Bobby On Fri, 25 Feb 2011 05:37:58 -0600, Bill Rowe <readnews at sbcglobal.net> wrote: > On 2/24/11 at 6:21 AM, darreng at wolfram.com (Darren Glosemeyer) wrote: > >> On 2/23/2011 4:24 AM, Bill Rowe wrote: > >>> But if I enter each line by hand into individual cells, I don't see >>> the error. So, there appears to be a bug somewhere. That is, the >>> various ways I've described above of doing the computation should >>> all behave identically. > >> ProbabilityScalePlot and its friends call the internal parameter >> estimation code for FindDistributionParameters/EstimatedDistribution >> to get the estimates. The reason for the message is that the >> equations in the estimation code for WeibullDistribution were less >> numerically stable than they could have been and so convergence >> fails more often than it should when parameter values are somewhat >> large. This has been fixed for the next release. > >> I think the fact that the example worked without error when you >> typed the inputs in separate cells is a red herring. The example >> will converge for some data sets and not for others. I suspect the >> random values you got in the case that worked just happened to give >> a convergent result while the random values you'd gotten in the >> other attempts did not. > > Your explanation makes sense and I should have thought about the > random number generator. But I was getting such consistent > results, this just didn't occur to me. Possibly part of the > reason I had never seen this in the past when I've used random > Weibull deviates I've been interested in smaller shape factors > (in the range of 0.2 to ~5). That also might change the > likelihood of getting values leading to the error. Additionally, > when I was attempting to isolate the problem, I was actually > quitting the kernel and restarting it so that each test started > with a fresh session. This too, might have had an affect on how > likely it was to get a set of values that lead to the error message. > > -- DrMajorBob at yahoo.com