fit_sraplus | R Documentation |
The main function for taking an object created by format_driors
and fitting a surplus production
model using sraplus
fit_sraplus(
driors,
include_fit = TRUE,
seed = 42,
plim = 0.05,
model_name = "sraplus_tmb",
randos = "log_proc_errors",
draws = 1e+05,
n_keep = 2000,
engine = "sir",
cores = 4,
chains = 1,
cleanup = FALSE,
max_treedepth = 10,
adapt_delta = 0.8,
estimate_shape = FALSE,
estimate_qslope = FALSE,
estimate_q = TRUE,
estimate_proc_error = TRUE,
estimate_initial_state = TRUE,
estimate_k = TRUE,
estimate_f = FALSE,
learn_rate = 0.001,
analytical_q = FALSE,
use_baranov = TRUE,
include_m = FALSE,
ci = 0.89,
try_again = FALSE,
eps = 1e-06,
max_time = Inf,
eval.max = 200,
iter.max = 150,
rel.tol = 1e-10,
loopnum = 2,
newtonsteps = 0,
tune_prior_predictive = TRUE,
index_fit_tuner = "sir",
refresh = 250,
log_bias_correct = TRUE,
workers = 1,
thin_draws = FALSE,
thin_rate = 0.5,
catch_cv = 0.01,
non_centered = FALSE,
...
)
driors |
a list of driors passed from sraplus::format_driors |
include_fit |
logical indicating whether to return the fitted object |
seed |
seed for model runs |
plim |
cutoff (in units of B/K) for hockey stick PT function |
model_name |
the name of the sraplus TMB version to be run, defaults to "sraplus_tmb" |
randos |
random effects when passing to TMB |
draws |
the number of SIR samples to run |
n_keep |
the number of SIR samples to keep |
engine |
one of 'sir','stan', or 'tmb' |
cores |
number of cores for stan fits |
chains |
number of chains for stan fits |
cleanup |
logical indicating whether to remove the compiled TMB model after running |
max_treedepth |
max_treedepth for models fit using stan |
adapt_delta |
adap_delta for models fit using stan |
estimate_shape |
logical indicating whether to estimate the shape parameter of the Pella-Tomlinson model. If FALSE shape parameter is held at the initial value, either default or supplied |
estimate_qslope |
logical indicating whether to estimate a slope parameter for q in CPUE fitting.
If FALSE q_slope is held at the initial value, either default or supplied. if TRUE, |
estimate_q |
estimate catchability coefficient or leave fixed |
estimate_proc_error |
logical indicating whether to estimate process errors. If FALSE process errors are not included in the model |
estimate_initial_state |
|
estimate_k |
estimate carrying capacity |
estimate_f |
estimate fishing mortality |
learn_rate |
learn_rate for HMC |
analytical_q |
use analytical q instead of empirical |
use_baranov |
use baranov catch equation |
include_m |
include natural mortality (deprecated) |
ci |
confidence/credible interval range for summaries |
try_again |
try fit again with adjusted starting guess |
eps |
eps for nlminb |
max_time |
max_time for nlminb |
eval.max |
eval.max for nlminb |
iter.max |
iter.max for nlminb |
rel.tol |
for nlminb |
loopnum |
for nlminb |
newtonsteps |
for TMBhelper |
tune_prior_predictive |
tune prior predictive to resolve borel's paradox |
index_fit_tuner |
"sir" tunes priors for index fit |
refresh |
refresh rate for Stan |
log_bias_correct |
correct for log-transformation bias |
workers |
number of workers for parallel processing of stan outputs |
thin_draws |
true or false thing draws |
thin_rate |
thinning rate |
catch_cv |
assumed CV for catch data when estimating catches rather than treating as data |
non_centered |
use centered or non-centered form for process errors |
... |
additional parameters |
a fitted sraplus object
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.