Commonly used adaptation methods #20
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Adding a class containing commonly used parameters and methods to adapt them (for static Bayesian models).
src/staticModelAdapt.cpp
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| /// \param desiredCESS The target conditional ESS for the next temperature (generally fixed). | ||
| void staticModelAdapt::ChooseTemp(const arma::vec & logweight, const arma::vec & loglike, double desiredCESS) { | ||
| double temp_curr = temp.back(); | ||
| if (CESSdiff(logweight,loglike,1-temp_curr,desiredCESS)>=0){ |
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Might it make sense for the comparison to be with -0.01 (or the tolerance) to be consistent with the inner workings of the bisection function?
src/staticModelAdapt.cpp
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| m = (a+b)/2.0; | ||
| f_m = CESSdiff(logweight,loglike,m-curr,desiredCESS); | ||
| err = 10; | ||
| while (err > 0.01){ |
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It might be good if it were possible to choose this tolerance without changing a hard-coded constant. In some applications the desired CESS might be larger than 0.99 and a tolerance of 0.01 would be problematic in those settings.
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Thanks Adam for this and for all of your other good points. I should have picked up on at least some of these myself -- sorry about that. I've changed this and a couple of other minor things (like writing 1.0 instead of 1 if it's a double) and will do another commit when the check finishes.
| /// \param desiredAcceptProb The desired probability of a successful move for each particle. | ||
| /// \param initialN The initial number of MCMC repeats. | ||
| /// \param maxReps The maximum number of MCMC repeats. | ||
| int staticModelAdapt::calcMcmcRepeats(double acceptProb, double desiredAcceptProb, int initialN, int maxReps){ |
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It's a bad idea to compare doubles with integers using ==, usually (the finite precision issue), might it make sense to replace these comparisons with
abs(acceptProb - 1) <= 10**-9
or similar?
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Great, thanks. |
Adding a class containing commonly used parameters and methods to adapt them (for static Bayesian models).