The latest release of the SAMtool package is available on CRAN.
RCM2MOM
converts the output of RCM
to a
multi-fleet operating model.RCM_assess
for using the RCM
model as an assessment in closed-loop projections. More arguments will
be added in the future for flexibility with model configuration.make_project_MP
creates management procedures that
update TAC annually from stock assessment projections.posterior
wrapper function added to run MCMC of RCM
models. RCMstan
updates OMs with MCMC output.Shortcut
and Perfect
assessment functions.HCR_segment
with yield per recruit
(F01 and Fmax).interim_MP
include adding NULL catch for
catch advice and adding missing feature to report assessment output when
diagnostic = 'full'
.HCR_segment
and
HCR_ramp
.R0
and log(R0)
for RCM models and assessment models.RCM
only
enter the objective function once.RCM
reporting.SCA_RWM
can accept multiple years to the
refyear
argument, e.g.,
expression(1:Data@Year)
. The model will calculate reference
points (MSY, unfished values, and steepness) using the mean M during the
specified years.NA
in
Rec@TAC
when multiple assessments do not converge.Shortcut
indexing to align year of assessment
with projection. An MP using the Perfect
assessment and
HCR_MSY
annually will produce F = FMSY in the OM.VPA
when the catch-at-age in the plusgroup
and plusgroup-1 is very small.RCM
will check age and length comp data for NA’s and
replaces with zeroRCM
reports annual equilibrium unfished reference
points using constant stock recruit alpha and betamake_interim_MP
function is added to generate MPs
that adjust the TAC between periodic assessments using the index.SP
is added to avoid negative
biomass situations.RCM
so that the mean is one in normal space. This error was
apparent when autocorrelation was very large.HCR_segment
allows for creating control rules with any
number of linear segments.RCM
.RCMdata
, is used to send data to the
RCM model, i.e., RCM(OM, RCMdata)
. For now, backwards
compatibility should still be maintained when feeding a data list (used
prior to v1.2) to fit the model.profile
generic is now available for
RCM
models. Steepness, R0, and final depletion can be
profiled.compare_RCM
.RCM
are now lognormal instead of
normal.Catch
, CAA
, and CAL
in addition
to Index
in a named list LWT
. Backwards
compatibility remains to provide LWT
as a vector for index
likelihood weights only.SCA_DDM
) is added.SCA_CAL
) is added.MW = TRUE
. The functions
will look for mean weight data series in Data@Misc[[x]]$MW
,
otherwise will convert length composition Data@CAL
to
weights and calculate annual means.Shortcut2
). This function fits an
SCA assessment and then characterizes the assessment error relative to
the operating model using a vector autoregressive (VAR) model. The
functions samples the operating model with error predicted from the VAR
model for the projection period. This is a useful function to guide the
level of error in the shortcut method.HCR_ramp
are available to
create harvest control rules based on dynamic B0, and F-based rules
(F/FMSY, F/F01, F/F-SPR).HCR_escapement
).RCM
will now
incorporate catches into the likelihood as a default. This allows the
model to estimate F and R0 when conditioned on effort and there is
patchy catch data.multiMSE
remains in MSEtool.SCA
,
SCA_Pope
, SSS
) start at age 0 following the
change in the MSEtool OM.SCA_RWM
) can be used to
estimate time-varying M (constant with age) as a random walk. Fix the
random walk SD to a low value to effectively estimate a time-constant M
(see help page).nlminb
) are turned off. Convergence status and issues can
be checked in the conv
slot of the output Assessment
object. In closed-loop simulation, the diagnostic
function
can be used to track the behavior of model-based MPs. By default,
pre-packaged model-based MPs and MPs made from the make_MP
function are designed to report convergence info (stored in
MSE@PPD
).Shortcut
assess function samples the OM with error
and autocorrelation for HCRs as an emulator of a stock assessment in
closed-loop simulation. The Perfect
function samples the OM
without error.AddInd
argument of functions which
index slots in the Data object will be used among Data@Ind, Data@SpInd,
Data@VInd, and Data@AddInd. Within series weighting is applied by using
the corresponding CV slot, i.e., Data@CV_Ind for Data@Ind, etc. Among
series weighting can also be tuned using likelihood weights with
LWT
argument. For SCA and VPA models, the selectivity is
fixed in the model using Data@AddIndV for indices in Data@AddInd.RCM
(Rapid Conditioning Model).maxage + 1
which
corresponds to ages 0 to maxage.condition = "catch"
), the likelihood for the catch can now
have a user-defined standard deviation indicated in
data$C_sd
(year and fleet specific, the previous default
was 0.01 was built-in for all catches).OM@cpars$LatASD
.