invert_bt.RdUse samplers from the BayesianTools package to fit models to data. Like
invert.auto, this will continue to run until convergence is achieved
(based on Gelman diagnostic) and the result has enough samples (as
specified by the user; see Details).
invert_bt(observed, model, prior, custom_settings = list(), loglike = NULL)
| observed | Vector of observations. Ignored if |
|---|---|
| model | Function called by log-likelihood. Must be |
| prior | BayesianTools prior object. |
| custom_settings | Nested settings list. See Details. |
| loglike | Custom log likelihood function. If |
custom_settings is a list of lists, containing the following:
common -- BayesianTools settings common to both the initial and subsequent samples.
init -- BayesianTools settings for just the first round of sampling.
This is most common for the initial number of iterations, which is the
minimum expected for convergence.
loop -- BayesianTools settings for iterations inside the convergence
checking while loop. This is most commonly for setting a smaller
iteration count than in init.
other -- Miscellaneous (non-BayesianTools) settings, including:
sampler -- String describing which sampler to use. Default is DEzs
use_mpsrf -- Use the multivariate PSRF to check convergence.
Default is FALSE because it may be an excessively conservative
diagnostic.
min_samp -- Minimum number of samples after burnin before stopping.
Default is 5000.
max_iter -- Maximum total number of iterations. Default is 1e6.
lag.max -- Maximum lag to use for autocorrelation normalization.
Default is 10 * log10(n) (same as stats::acf function).
save_progress -- File name for saving samples between loop
iterations. If NULL (default), do not save progress samples.
threshold -- Threshold for Gelman PSRF convergence diagnostic. Default is 1.1.
verbose_loglike -- Diagnostic messages in log likelihood output. Default is TRUE.
See the BayesianTools sampler documentation for what can go in the BayesianTools settings lists.