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View Code? Open in Web Editor NEWApproximate Bayesian Computation (ABC) with differential evolution (de) moves and model evidence (Z) estimates.
License: MIT License
Approximate Bayesian Computation (ABC) with differential evolution (de) moves and model evidence (Z) estimates.
License: MIT License
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Release to update compat helper suggested StatsBase.jl dependency change.
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implements #5, to be released with v0.2.0 as new main feature; does not break previous code, but induces changed behaviour. Kmcmc
steps may early exit due to new Kmcmc_min
; output of abcdesmc!
method now additionally contains Kmcmcs
info.
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below a collection of potential improvements for future releases.
IndicatorStrict0toϵ
) for the SMC method. without strictness (i.e. with the current default Indicator0toϵ
kernel) the SMC alg. sometimes gets stuck if particle numbers are on the lower side. disadvantage is that the non-strict kernel is better for small discrete problems where perfect convergence may be reached with ABC; but this case is rare in practice, hence I could just document the kernel choice more for directing users appropriately and switch to the strict kernel.any further suggestions are very very welcome!
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Look into the possibility to set a high Kmcmc
keyword argument in abcdesmc!
method, with an option (new keyword argument) to early exit the MCMC iterations when a sufficiently high number of acceptances (as provided/desired) has already been reached.
This may help to diversify particles better at the last epsilon steps (higher Kmcmc
), without adding too much unnecessary computation load at the first iterations (using early exit). See into smc
at KissABC where something similar exists.
Potentially also write the actual number of used MCMC steps into the results object (if verboseout=true
).
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