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: [hidden email] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
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. ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
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. > ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
> On Mar 19, 2019, at 2:06 PM, Evan Cooch <[hidden email]> wrote: > > 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. >> > Evan, While I cannot speak for the R-Help moderators, which is a 'larger' group, I am a co-moderator for R-Devel. The initial moderation occurs when someone who has not subscribed to the list sends a post. The list software captures the post and sends the moderators a notification that there is a post from a non-subscriber requiring manual review. If the post is not relevant to the specific R list and should be sent to another R list, where it is better suited given the focus of the topic, the post will be rejected and the poster informed of the reason. If it is not truly R related, per se, then a recommendation to send the post to StackExchange or similar will be send back to the poster, with a rejection of the post. Once a sender's e-mail account has been approved to post, which generally means that they have both subscribed to the list in question and have sent at least one relevant post to the list, future posts are typically no longer moderated. It is possible that once in a while, a moderator will miss something in the post content and approve it going to the list, but that should be a rare event. A search of the R-Help archives suggests that Philip has posted previously, going to back at least 2011, which is likely why this particular post managed to not be moderated. Regards, Marc Schwartz ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In reply to this post by Evan Cooch
Actually the list is not moderated in the usual sense of the word. If
you subscribe, your posts are not moderated. Only your first posting after subscription would be moderated, but for the purpose of preventing persons with obvious spamming goals. And there are several different moderators. If I had seen that posting, I might have rejected it. -- David. On 3/19/19 11:06 AM, Evan Cooch wrote: > 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. >> > > ______________________________________________ > [hidden email] mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In reply to this post by philip_rhoades
Highly off topic. Try StackOverflow.
On March 19, 2019 10:42:24 AM PDT, Philip Rhoades <[hidden email]> 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. ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
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 <[hidden email]> 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. ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
David,
On 2019-03-20 12:38, David Winsemius wrote: > 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) Thanks - I will check that out . . P. > -- > > David. > >> >> On March 19, 2019 10:42:24 AM PDT, Philip Rhoades <[hidden email]> >> 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. -- Philip Rhoades PO Box 896 Cowra NSW 2794 Australia E-mail: [hidden email] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
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