[HN Gopher] Markov Chain Monte Carlo analysis of climate-change ...
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       Markov Chain Monte Carlo analysis of climate-change variables
        
       Author : bryanrasmussen
       Score  : 72 points
       Date   : 2022-02-06 13:45 UTC (9 hours ago)
        
 (HTM) web link (www.nature.com)
 (TXT) w3m dump (www.nature.com)
        
       | ashtonbaker wrote:
       | If you want a tutorial/framework for MCMC analysis, check out the
       | R package "pomp":
       | 
       | https://kingaa.github.io/pomp/docs.html
        
         | epgui wrote:
         | How does pomp compare to mc-stan? I thought that was the
         | preferred tool these days. https://mc-stan.org/
        
       | savant_penguin wrote:
       | Pardon my ignorance, but why do you need mcmc to analyze
       | sensitivity? Isn't sensitivity something related to the
       | derivative of the output with respect to the parameter?
        
         | contravariant wrote:
         | There's no reason you couldn't take the expectation value of a
         | derivative. Linearity of expectation means this will be equal
         | the derivative of the expectation value.
         | 
         | I may be missing the point though; I'm only versed in the
         | mathematics.
        
         | shane_b wrote:
         | I believe this is because not all derivatives are possible via
         | calculation and mcmc gives close approximation. But I could
         | misunderstand.
        
         | rich_sasha wrote:
         | Perhaps this is to do with parameter calibration? If you vary
         | parameters until you get best fit, then use them to forecast
         | forward, you will hugely understate the variation, and very
         | possibly also bias the estimate.
        
         | digikata wrote:
         | When you have many parameters in multiple models with
         | interdependent parameters in feedback cycles the Monte Carlo
         | method lets you sample the space and explore faster. Especially
         | in large scale simulations the execution speed limits
         | exhaustively computing your way through the parameter space.
         | 
         | And because there is likely no simple set gradients to follow,
         | I'd suspect the Markov probabilities let you further navigate
         | local maxima and minima more effectively. Something like a
         | breadcrumb trail of past paths through the forest.
        
         | sanxiyn wrote:
         | Yes, but we don't have a differentiable climate model. People
         | are working on it, but it's not there yet. See
         | https://clima.caltech.edu/ and https://dj4earth.github.io/.
        
       | bryanrasmussen wrote:
       | original title "Sensitivity of non-conditional climatic variables
       | to climate-change deep uncertainty using Markov Chain Monte Carlo
       | simulation" obviously too long, had a hard time finding a title
       | that fit so if you can think of a better one I can edit if within
       | window.
        
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       (page generated 2022-02-06 23:01 UTC)