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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.
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