I have tried to convert the attached MC15 worksheet to SMATH. I cannot work around the solve block (Maximize) successfully. I welcome the collabs review and recommendation(s).
Sincerely,
nas
File non trovato.File non trovato.

The solve block is in the "Weibull Distribution" area (collapsed).
nas

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I have tried to convert the attached MC15 worksheet to SMATH.

Smath converts zero, absolute zero MCD.
You have to create the project from square one .
At least, you can plot 3 graphs

If I force the shape and scale factors all seems to work. I just need help with obtaining these.Chain Failure Weibull Analysis Forced.sm (66,59 KiB) scaricato 1152 volta(e).

Chain Failure Weibull Analysis Forced.sm (71,24 KiB) scaricato 1195 volta(e).

I noticed that my previous SMATH files lacked some narrative. Updated now.

Thank you,

Chain Failure Weibull Analysis - 2.sm (52,74 KiB) scaricato 1222 volta(e).

Taking jmg's advice; started going thru the steps and found a function that didn't come over from MC that I used the wrong "Sum" function in SMATH. Worksheet function ll.W(....) now seems to work plotting varying lambda and beta (sheet attached). I still cannot determine/maximize the function, finding the optimim lambda and beta.

I welcome any suggestions.

nas

Hi. Try this. Chain Failure Weibull Analysis - 3.sm (65,78 KiB) scaricato 1187 volta(e).

Alvaro.

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I still cannot determine/maximize the function, finding the optimim lambda and beta.

Is that what you mean: that the n*F.W(x,λ,β) is the best fit to data {TY] ?
Very rarely, a model function can be declared exact. That is the case of all LS based methods.
I guess the data set [TY] can be fitted by many models, surely giving λ,β closely to Alvaro.
Easy to plot [TY] over the n*F.W(x,λ,β) ... module added .
Interesting but not of immediate understanding for the novice.

Cheers ... Jean
Opened in 6179, re-posted from same original.

Chain Failure Weibull Analysis - 3.sm (71,05 KiB) scaricato 1209 volta(e).

Fit using Maxima's lsquares package. MSE() is the mean square error, which is minimized by Fit()


Chain%20Failure%20Weibull%20Analysis%20-%203_Kr.sm (78,46 KiB) scaricato 1358 volta(e).

Alvaro, jmg and Martin, many thanks!

Martin's requires a newer version of SMATH installed, I'll have to request the upgrade to be installed.

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Alvaro, jmg and Martin, many thanks!

Martin's requires a newer version of SMATH installed, I'll have to request the upgrade to be installed.

Should work with SMath build 6671 as well (latest stable with updated plug-ins), just ignore the complaints.

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Martin's requires a newer version of SMATH installed,

Maybe NOT ... Maybe I'm too ignorant about Weibull.
What I understand: over 'T', you have observed cumulative failure, is it ?
From there you can approximate the probability of failures from the logistic Verhulst.
I would be curious you find simpler and more realistic and more immediate insight.
Done Smath 6971, should work in more recent SS.

Cheers ... Jean

Page0Weibull.sm (40,2 KiB) scaricato 1252 volta(e).

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What I understand: over 'T', you have observed cumulative failure, is it ?

Not like said. The 'Y' data are the days between failure.
Refreshed and added the cumulative integration of the Verhulst fit.

Genfit Weibull.sm (45,44 KiB) scaricato 1200 volta(e).

Thank you Jean, I have a lot to look over. I noticed that the MC file calculated a beta > than 1, which is a "wear-out" characteristic vs. the SMATH beta <1; "infant mortality". I found an earlier MC file that used a different method to find beta, and that too beta was < 1. Using excel, that was also in agreement; beta < 1. The values vary, the old MC file = 0.99, 0.98 for the SMATH file, and .99 for excel.

I use the files as a reference, being a novice using tools for stats. I did get a lot of new ideas and understand more using SMATH, which I am thankful to this collab.

Sincerely,

Norm

Hello Jean, Beta will not calculate, I have the same SMATH version 0.99.6671. Maybe I'm missing a plugin?

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"infant mortality"

... because there 3 kinds of lies:
1. Kid's white lie [Mamy, Mamy ... the cat did suck your last candy]
2. True lies [Politician's lie]
3. Statistics

What happens in the β "infant mortality" is consequence of
reflexivity in the function wrt parameters. Many models
can't be concluded by NO maths ... just manual from St. Patience !

If you stick with Weibull failure analysis, good luck.
In about ½ hr I found nothing from Gooling.

Sorry Jean, your genfit file won't find beta. It works fine when I download, but fails when I open on my pc.

nas

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Sorry Jean, your genfit file won't find beta. It works fine when I download, but fails when I open on my pc.

1. The work sheet attached finds the β's of the Verhulst logistic function,
which corresponds to your collection. For the two parameters Weibull, we have
to scale the Y data to [0..1] and the X data to something else.
Your project up until now is just an undefined collection.
I will attempt a pure Weibull fit.

2. Can't understand it works fine from download but fails on your PC.
Like saying: moon is flat because she is flat as well as spherical
because she is spherical. Just circular like Shrodinger cat ...
hit the cat he is dead, hit again back live.

Cheers ... Jean

Stat Treasury_7 Weibull.sm (9,3 KiB) scaricato 1170 volta(e).

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I will attempt a pure Weibull fit.

... here is a typical two parameters Weibull

Stat Treasury_7 Weibull.sm (18,69 KiB) scaricato 1152 volta(e).

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... here is a typical two parameters Weibull

... too reactive for :Genfit Minimize.
Thus: simply manual fit by the look.

Stat Treasury_7 Weibull.sm (20,74 KiB) scaricato 1201 volta(e).