Show Posts
1
Damage & Loss (PELICUN) / Uncertainty in consequence models
« on: April 14, 2022, 12:54:41 AM »
Hello Adam,
Thanks a lot for the new updates and versions of Pelicun (specially the tutorial), it has been really helpful. I’ve been working on the tutorial you posted on youtube for a while now and I have a couple of questions regarding the definition of uncertainties.
1.- How can I specify uncertainty in the consequence models? I tried doing this by specifying a family and a Theta 1 value in the collapse/replacement consequences (additional_consequences dataframe in the tutorial), but when I do this, I notice that I still get a deterministic value for all the collapse/replacement realizations. In addition, some of the default FEMA P-58 components have already uncertainty defined and when the analysis is run, all the consequences (replacement costs) are still deterministic. Do you have any recommendations? I’m probably missing something here...
2.- It is mentioned in the tutorial that Pelicun supports many distributions. Does it support skew normal distribution as well? If so, how can I define it? My initial thought was to have Theta_0, Theta_1 and Theta_2 that represents shape, loc and scale of my distribution but I don’t know if this is possible.
Any help will be greatly appreciated! Thanks a lot!
Best,
Andrés Ramos.
Thanks a lot for the new updates and versions of Pelicun (specially the tutorial), it has been really helpful. I’ve been working on the tutorial you posted on youtube for a while now and I have a couple of questions regarding the definition of uncertainties.
1.- How can I specify uncertainty in the consequence models? I tried doing this by specifying a family and a Theta 1 value in the collapse/replacement consequences (additional_consequences dataframe in the tutorial), but when I do this, I notice that I still get a deterministic value for all the collapse/replacement realizations. In addition, some of the default FEMA P-58 components have already uncertainty defined and when the analysis is run, all the consequences (replacement costs) are still deterministic. Do you have any recommendations? I’m probably missing something here...
2.- It is mentioned in the tutorial that Pelicun supports many distributions. Does it support skew normal distribution as well? If so, how can I define it? My initial thought was to have Theta_0, Theta_1 and Theta_2 that represents shape, loc and scale of my distribution but I don’t know if this is possible.
Any help will be greatly appreciated! Thanks a lot!
Best,
Andrés Ramos.