Description Usage Arguments Details
Use 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).
1 |
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.
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