Description Usage Arguments Value
Run an MCMC using an ADMB model, return (1) the posterior draws, MLE fits and covariance/correlation matrices, and some MCMC convergence diagnostics using CODA.
Run an MCMC using an ADMB model, return (1) the posterior draws, MLE fits and covariance/correlation matrices, and some MCMC convergence diagnostics using CODA.
1 2 3 4 5 6 7 8 9 10 11 | run_admb_mcmc(model.path, model.name, iter, mcsave, burn.in, cov.user = NULL,
init.pin = NULL, se.scale = NULL, mcscale = FALSE, mcseed = NULL,
mcrb = NULL, mcdiag = FALSE, mcprobe = NULL, verbose = TRUE,
extra.args = NULL, hybrid = FALSE, hyeps = NULL, hynstep = NULL,
mceval = FALSE, estimate = FALSE)
run_admb_mcmc(model.path, model.name, iter, mcsave, burn.in, cov.user = NULL,
init.pin = NULL, se.scale = NULL, mcscale = FALSE, mcseed = NULL,
mcrb = NULL, mcdiag = FALSE, mcprobe = NULL, verbose = TRUE,
extra.args = NULL, hybrid = FALSE, hyeps = NULL, hynstep = NULL,
mceval = FALSE, estimate = FALSE)
|
model.path |
(Character) A path to the folder containing the model. NULL indicates the current folder. |
iter |
(Integer) The number of draws after thinning and burn in. |
mcsave |
(Integer) Controls thinning of samples. Save every mcsave value, such that 1 corresponds to keeping all draws, and 100 saving every 100th draw. |
burn.in |
(Integer) How many samples to discard from the beginning of the chain, *after* thining. The burn in period (i.e., the first burn.in*mcsave draws) should be at least large enough to cover dynamic scaling. |
cov.user |
(Numeric matrix) A manually defined covariance matrix (in bounded space) to use in the Metropolis-Hastings algorithm. |
init.pin |
(Numeric vector) A vector of initial values, which are written to file and used in the model via the -mcpin option. |
se.scale |
(Numeric) A value which scales all of the variances from the MLE fit. A value of 1 indicates to use the estimated variances. |
mcscale |
(Logical) Whether to use the mcscale option, which dynamically scales the covariance matrix for efficient acceptance ratios. |
mcseed |
(Integer) Which seed (integer value) to pass ADMB. Used for reproducibility. |
mcrb |
(Integer) Which value to use in the rescale bounded algorithm. Must be an integer from 1-9. The default NULL value disables this feature. See the vignette for more information on this algorithm and how to best use it. |
mcdiag |
(Logical) Whether to use the |
verbose |
(Logical) Whether to print ADMB warnings and other information. Useful for testing and troubleshooting. |
extra.args |
(Character) A string which is passed to ADMB at runtime. Useful for passing additional arguments to the model executable. |
hyeps |
(Numeric) The size of the leapfrog jump in the hybrid method, with smaller values leading to smaller but more accurate jumps. Must be a positive value. |
hynstep |
(Integer) The approximate number of steps used in the
leapfrog step of the hybrid algorithm. Steps are randomly generated for
each MCMC iteration, centered around |
mode.name |
(Character) The name of the model executable. A character string, without '.exe'. |
thin |
(Integer) Controls thinning of samples. Save every thin value, such that 1 corresponds to keeping all draws, and 100 saving every 100th draw. |
warmup |
(Integer) How many samples to discard from the beginning of the chain, *after* thining. The burn in period (i.e., the first warmup*thin draws) should be at least large enough to cover dynamic scaling. |
init |
(Numeric vector) A vector of initial values, which are written to file and used in the model via the -mcpin option. |
eps |
(Numeric) The size of the leapfrog jump in the hybrid method, with smaller values leading to smaller but more accurate jumps. Must be a positive value. |
model.path |
(Character) A path to the folder containing the model. NULL indicates the current folder. |
mode.name |
(Character) The name of the model executable. A character string, without '.exe'. |
iter |
(Integer) The number of draws after thinning and burn in. |
cov.user |
(Numeric matrix) A manually defined covariance matrix (in bounded space) to use in the Metropolis-Hastings algorithm. |
mcseed |
(Integer) Which seed (integer value) to pass ADMB. Used for reproducibility. |
mcdiag |
(Logical) Whether to use the |
hyrbid |
(Logical) Whether to use the Hamiltonial (hybrid) algorithm. Default is FALSE. |
verbose |
(Logical) Whether to print ADMB warnings and other information. Useful for testing and troubleshooting. |
extra.args |
(Character) A string which is passed to ADMB at runtime. Useful for passing additional arguments to the model executable. |
Returns a list containing (1) the posterior draws, (2) and
object of class 'admb', read in using the results read in using
read_admb
, and (3) some MCMC convergence diagnostics using CODA.
Returns a list containing (1) the posterior draws, (2) and
object of class 'admb', read in using the results read in using
read_admb
, and (3) some MCMC convergence diagnostics using CODA.
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