Description Usage Arguments Details Value
Inversion with automatic convergence checking
1 2 3 4 5 6 7 8 9 10 |
observed |
Vector, matrix, or data frame (coerced to matrix) of
observed values. For spectral data, wavelengths are rows and spectra are
columns. Dimensions must align with the output of |
invert.options |
Parameters related to inversion. |
return.samples |
Include full samples list in output. Default = |
save.samples |
Save samples to file as the inversion proceeds (useful
for debugging). If |
quiet |
Suppress progress bar and status messages. Default=FALSE |
parallel |
Logical. Whether or not to run multiple chains in parallel
on multiple cores (default = |
parallel.cores |
Number of cores to use for parallelization. If
|
parallel.output |
Filename (or ” for stdout) for printing parallel
outputs. Use with caution. Default = |
Performs an inversion via the invert.custom
function with
multiple chains and automatic convergence checking. Convergence checks are
performed using the multivariate Gelman-Rubin diagnostic.
Parameters specific to invert.auto
are described here.
For the remaining parameters, see invert.custom()
.
model
– The model to be inverted. This should be an R function that
takes params
as input and returns one column of observed
(nrows should be the same). Constants should be implicitly included here.
nchains
– Number of independent chains.
inits.function
– Function for generating initial conditions.
ngibbs.max
– Maximum number of total iterations (per chain). DEFAULT = 5e6
ngibbs.min
– Minimum number of total iterations (per chain). DEFAULT = 5000.
ngibbs.step
– Number of iterations between convergence checks. Default = 1000.
run_first
– Function to run before running sampling. Takes parallel
inputs list containing runID, initial values, and resume (NULL) as an
argument.
calculate.burnin
– If TRUE
, use PEcAn.assim.batch::autoburin
function to calculate burnin. Otherwise, assume burnin is min(niter/2, iter_conv_check)
.
threshold
– Maximum value of the Gelman-Rubin diagnostic for
determining convergence. Default = 1.1
List including results
(summary statistics), samples
(mcmc.list
object, or NA
if return.samples=FALSE
), and other
information.
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