Comments (2)
Hey Nick (@nmatzke),
thanks for your suggestion. Glad you like the package!
About your question:
Currently there is the possibility to update parameter blocks in
the DE(zs) sampler. Insted of random subset as this is being done in
DREAM(zs) you can either update blocks based on correlations or
define your own blocks.
You'll find some more information in the help page of DE(zs).
Hope this helps a bit.
Best,
Stefan
from bayesiantools.
To add to this - there are also some advanced options to tune the Gibbs update in the Metropolis (e.g. to move more than 1 parameter at a time, see help). Also, the Metropoli actually allows custom proposal functions, as long as they have the same interface as the built-in proposal. However, this is not properly documented, and we don't check user-provided functions, so I would not recommend it at the moment.
Nick, would be good to get your feedback if you play around with these things.
Independent of that, we could put
- unify blocking options across samplers
- provide the possibility to specify custom proposals
on the list of long-term goals - until this this is better specified, I'll keep this ticket open.
from bayesiantools.
Related Issues (20)
- Pass on extra arguments to the likelihood HOT 4
- Unwritable Outputs For Some Random Seeds HOT 7
- CRAN problem (HTML5)
- Combine DE and DEzs code
- CRAN requires HTML5 for documentation HOT 1
- Add red card dataset to DHARMa?
- Metropolis sampler startup error: Matrix seems negative semi-definite HOT 1
- No longer on CRAN HOT 2
- Incoming CRAN / win builder checks - detritus in temp directory HOT 3
- bridgesample function neccessary? HOT 2
- Questions about BT
- Simulation-based calibration HOT 1
- How to tell if the parallel computation is actually turned on HOT 7
- Number of calls to likelihood function HOT 1
- CRAN DHARMa.Rd issue HOT 3
- Vignette - should there be an example for convergence check?? HOT 1
- Examples in Vignette with eval = F intentional? HOT 1
- Spatially constrained priors? HOT 3
- AR1 function sd estimate wrongly scaled HOT 3
- Writing a hierarchical model - unsure where to assign population-level parameters
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