### Author Topic: Discrete Boolean nodes with beliefs as data distributions?  (Read 5227 times)

#### Marko Gerbec

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• Posts: 3
##### Discrete Boolean nodes with beliefs as data distributions?
« on: January 05, 2015, 17:04:32 »
As a novice Hugin user and oriented to risk modelling applications, I am interested in using Boolean variables/nodes, however, the point values specified for parents for true and false states seem dull. Is it possible somehow to use "simple" distribution data (e.g, log-normal) for true state(s) and rest to 1 is set to false state?
Had read the Expressions chapter in Manual, and Distrubution () function as permitted for Boolean nodes is not clear enough for me.
« Last Edit: January 05, 2015, 17:06:05 by Marko Gerbec »

#### Frank Jensen

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• Posts: 575
##### Re: Discrete Boolean nodes with beliefs as data distributions?
« Reply #1 on: January 09, 2015, 20:39:28 »
It isn't clear to me what you're trying to achieve.  Could you give some examples?

#### Marko Gerbec

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• Posts: 3
##### Re: Discrete Boolean nodes with beliefs as data distributions?
« Reply #2 on: February 09, 2015, 14:51:30 »
The point is simple.
Instead of using point values for Boolean type of variables, I would like to use distributions, where normal or log-normal are of practical interest.
That would add information on the confidence intervals for states od interest. This is usually practiced in engineering risk assessments, like using methods of fault tree and event tree analysis. Needless to say, we are mainly interested in failures becoming realized = true.

#### Frank Jensen

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##### Re: Discrete Boolean nodes with beliefs as data distributions?
« Reply #3 on: February 24, 2015, 00:32:15 »
I still don't understand.  All probabilities in a Bayesian network are point probabilities.

It is possible to express some uncertainty on a probability by adding a parent node representing the probability.  That parent node would typically be an interval node ranging from 0 to 1 and be given a distribution over that interval (such as a Beta distribution).

How would a Normal or a Log-Normal distribution be used for your purpose?

#### Marko Gerbec

• Newbie
• Posts: 3
##### Re: Discrete Boolean nodes with beliefs as data distributions?
« Reply #4 on: March 01, 2015, 18:41:40 »
Specifically, the boolean's variable true wold be represented by a log-normal distribution, e.g., using mean and error-factor (=sqrt of 95 and 5 percentiles quotient), or other "input" data.
« Last Edit: March 01, 2015, 18:45:29 by Marko Gerbec »