R help - Mar 2019 - A general question about using Bayes' Theorem for calculating the probability of The End of Human Technological Civilisation

People,

I have only a general statistics understanding and have never actually 
used Bayes' Theorem for any real-world problem.  My interest lies in 
developing some statistical approach for addressing the subject above 
and it seems to me that BT is what I should be looking at?  However, 
what I am specifically interested in is how such a work-up would be 
developed for a year-on-year situation eg:

I think it is likely that TEHTC could be triggered by a multi-gigaton 
release of methane from the Arctic Ocean and the Siberian Permafrost in 
any Northern Hemisphere Summer from now on (multiple physical and 
non-physical, human positive feedback loops would then kick in).

So, say my estimate (Bayesian Prior) is that for this coming (2019) NHS 
the chance of this triggering NOT occurring is x%.  The manipulation is 
then done to calculate the posterior for 2019 - but for every successive 
year (given the state of the world), isn't it true that the chance of a 
triggering NOT occurring in the NHS MUST go down? - ie it is just an 
argument about the scale of the change from year to year?

It seems to be that the posterior for one year becomes the prior for the 
next year?  Once the prior gets small enough people won't bother with 
the calculations anyway . .

Does anyone know of any existing work on this topic?  I want to write a 
plain-English doc about it but I want to have the stats clear in my head 
. .

Thanks,

Phil.
-- 
Philip Rhoades

PO Box 896
Cowra  NSW  2794
Australia
E-mail:  phil at pricom.com.au

Rhelp is not a forum for discussions of statistics. Instead it is for 
persons who have specific questions about the use of R.

Please read the list info page where you started the subscription 
process. And do read the Posting Guide. Both these are linked at the 
bottom of this response.

There are Web accessible forums that are set up to statistics.

-- 

David.

On 3/19/19 10:42 AM, Philip Rhoades wrote:
> People,
>
> I have only a general statistics understanding and have never actually 
> used Bayes' Theorem for any real-world problem.? My interest lies in 
> developing some statistical approach for addressing the subject above 
> and it seems to me that BT is what I should be looking at?? However, 
> what I am specifically interested in is how such a work-up would be 
> developed for a year-on-year situation eg:
>
> I think it is likely that TEHTC could be triggered by a multi-gigaton 
> release of methane from the Arctic Ocean and the Siberian Permafrost 
> in any Northern Hemisphere Summer from now on (multiple physical and 
> non-physical, human positive feedback loops would then kick in).
>
> So, say my estimate (Bayesian Prior) is that for this coming (2019) 
> NHS the chance of this triggering NOT occurring is x%.? The 
> manipulation is then done to calculate the posterior for 2019 - but 
> for every successive year (given the state of the world), isn't it 
> true that the chance of a triggering NOT occurring in the NHS MUST go 
> down? - ie it is just an argument about the scale of the change from 
> year to year?
>
> It seems to be that the posterior for one year becomes the prior for 
> the next year?? Once the prior gets small enough people won't bother 
> with the calculations anyway . .
>
> Does anyone know of any existing work on this topic?? I want to write 
> a plain-English doc about it but I want to have the stats clear in my 
> head . .
>
> Thanks,
>
> Phil.

Just curious -- if R-help is a moderated list (which? in theory , it is 
-- my posts have been 'modertated', to the degree that they aren't 
released to the list until someone approves them), and if these 
'statistics discussion' questions are inappropriate to the mission (as 
described), then...why isn't the 'moderator' (him/her/they) blocking
on
submission?

On 3/19/2019 1:59 PM, David Winsemius wrote:
> Rhelp is not a forum for discussions of statistics. Instead it is for 
> persons who have specific questions about the use of R.
>
> Please read the list info page where you started the subscription 
> process. And do read the Posting Guide. Both these are linked at the 
> bottom of this response.
>
> There are Web accessible forums that are set up to statistics.
>

Highly off topic. Try StackOverflow.

On March 19, 2019 10:42:24 AM PDT, Philip Rhoades <phil at pricom.com.au>
wrote:
>People,
>
>I have only a general statistics understanding and have never actually 
>used Bayes' Theorem for any real-world problem.  My interest lies in 
>developing some statistical approach for addressing the subject above 
>and it seems to me that BT is what I should be looking at?  However, 
>what I am specifically interested in is how such a work-up would be 
>developed for a year-on-year situation eg:
>
>I think it is likely that TEHTC could be triggered by a multi-gigaton 
>release of methane from the Arctic Ocean and the Siberian Permafrost in
>
>any Northern Hemisphere Summer from now on (multiple physical and 
>non-physical, human positive feedback loops would then kick in).
>
>So, say my estimate (Bayesian Prior) is that for this coming (2019) NHS
>
>the chance of this triggering NOT occurring is x%.  The manipulation is
>
>then done to calculate the posterior for 2019 - but for every
>successive 
>year (given the state of the world), isn't it true that the chance of a
>
>triggering NOT occurring in the NHS MUST go down? - ie it is just an 
>argument about the scale of the change from year to year?
>
>It seems to be that the posterior for one year becomes the prior for
>the 
>next year?  Once the prior gets small enough people won't bother with 
>the calculations anyway . .
>
>Does anyone know of any existing work on this topic?  I want to write a
>
>plain-English doc about it but I want to have the stats clear in my
>head 
>. .
>
>Thanks,
>
>Phil.
-- 
Sent from my phone. Please excuse my brevity.

On 3/19/19 12:49 PM, Jeff Newmiller wrote:
> Highly off topic. Try StackOverflow.

As it stands it's off-topic for SO. (You would just be making more work 
for those of us who know the rules but need 4 close votes for 
migration.)? Better would be immediately posting at CrossValidated.com 
(i.e., stats.stackexchange.com)

-- 

David.
>
> On March 19, 2019 10:42:24 AM PDT, Philip Rhoades <phil at
pricom.com.au> wrote:
>> People,
>>
>> I have only a general statistics understanding and have never actually
>> used Bayes' Theorem for any real-world problem.  My interest lies
in
>> developing some statistical approach for addressing the subject above
>> and it seems to me that BT is what I should be looking at?  However,
>> what I am specifically interested in is how such a work-up would be
>> developed for a year-on-year situation eg:
>>
>> I think it is likely that TEHTC could be triggered by a multi-gigaton
>> release of methane from the Arctic Ocean and the Siberian Permafrost in
>>
>> any Northern Hemisphere Summer from now on (multiple physical and
>> non-physical, human positive feedback loops would then kick in).
>>
>> So, say my estimate (Bayesian Prior) is that for this coming (2019) NHS
>>
>> the chance of this triggering NOT occurring is x%.  The manipulation is
>>
>> then done to calculate the posterior for 2019 - but for every
>> successive
>> year (given the state of the world), isn't it true that the chance
of a
>>
>> triggering NOT occurring in the NHS MUST go down? - ie it is just an
>> argument about the scale of the change from year to year?
>>
>> It seems to be that the posterior for one year becomes the prior for
>> the
>> next year?  Once the prior gets small enough people won't bother
with
>> the calculations anyway . .
>>
>> Does anyone know of any existing work on this topic?  I want to write a
>>
>> plain-English doc about it but I want to have the stats clear in my
>> head
>> . .
>>
>> Thanks,
>>
>> Phil.