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The latest release of the SAMtool package is available on CRAN.
RCM
in argument pbc_recdev
. The bias
correction from logspace to normal space is
exp(log_rec_dev[y] - 0.5 * bc_recdev[y] * sigmaR^2)
if the
year-specific rec dev is estimated.RCMdata@I_delta
slot to specify survey timing (0-1)
within year. Default assumption is zero is used which is consistent with
previous versions.RCM2MOM
(report selectivity at length array,
catch fractions).RCM_output
tab in plot(RCModel)
,
report simulations and convergence rate, and clean up comp plots.RCM(condition = "catch2")
,
introduced in version 1.6.0.RCM
updates to calculate fishery length comp when
CAL_n > 0
and protect plot.RCM
from empty
index vectors.Perfect
uses spawn_timing to calculate spawning biomass
(exp(-spawn_time * M)
) in the middle of projection year.
Note that perfect HCR implementation needs to iteratively re-calculate
the projection year biomass, B/BMSY, B/B0
(exp(-spawn_time * [Ftarget + M])
) when applying the HCR.
Recommend spawn_time = 0 to implement HCR perfectly.ObsPars$Isd
.spawn_time_frac
argument to RCM.RCM(map = list(q = c(1, 1)))
. This example allows sharing q
between 2 indices. Currently, q can only be an explicit estimated
parameter (map argument is an integer), solved analytically (map
argument is NA), or fixed to 1 (map argument is NA and additional
specification in RCMdata@abs_I).x^0.01 * (1 - x)^0.01
where x is the ratio of the length of
full selectivity to Linf or age of full selectivity to maxage.plot_composition(plot_type = "heat_residuals")
. Also
re-adjust default bubble residual size.SCA2
and VPA
.make_MP
don’t match
formal arguments in .Assess
and .HCR
hist
function will report NA rate
(percent of NA’s) in a vector. Seen in markdown reports.max
function excludes infinite values.
Primarily used when generating axes limits in markdown reports.Data
object is passed to
RCM
.resample = TRUE
with stochastic fits to
RCM
.dnorm(log(Shinge/min(SSB)), 0, 2)
for hockey-stick SRR when
the hinge point is less than the smallest SSB.RCMdata@Chist
. The
trivially small catch still allows predictions of fishery age
composition from Baranov equation.diagnostic
introduced in 1.5.0.simulate
method for RCM and assessment models.map
and start
arguments for
RCM
.pbapply
.RCM
using the Mesnil and
Rochet (2010) parameterization.r
and
MSY
for surplus production models.MSE
object.Data@CAL
check when using RCM
.Gmisc::fastDoCall
when fitting models, e.g.,
SP_Fox
. Gmisc
is a Suggests
package.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
.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.