Package index
Rapid Conditioning Model
A population model intended for conditioning operating models from datasparse to datarich applications.

check_RCMdata()
RCM()
 Rapid Conditioning Model (RCM)

RCM2MOM()
 Convert RCM to a multifleet operating model (MOM)
Management procedures
Make a management procedure from an assessment and control rule or use a suite of premade MPs.

make_interim_MP()
make_projection_MP()
make_MP()
 Make a custom management procedure (MP)

SCA_MSY()
SCA_75MSY()
SCA_4010()
DDSS_MSY()
DDSS_75MSY()
DDSS_4010()
SP_MSY()
SP_75MSY()
SP_4010()
SSS_MSY()
SSS_75MSY()
SSS_4010()
 Modelbased management procedures
Population models
Assessment models that can be fitted with a Data object for closedloop simulation.

SCA()
SCA2()
SCA_Pope()
 Statistical catchatage (SCA) model

SCA_CAL()
 Agestructured model using fishery length composition

SCA_DDM()
 SCA models with timevarying natural mortality

SCA_RWM()
 SCA with random walk in M

RCM_assess()
 The rapid conditioning model as an assessment function

SSS()
 Simple Stock Synthesis

Shortcut()
Shortcut2()
Perfect()
 Assessment emulator as a shortcut to model fitting in closedloop simulation

VPA()
 Virtual population analysis (VPA)

projection()
 Projections for assessment models
Harvest control rules
Functions to pair with an assessment model to create a catchbased managment procedure.

HCR_MSY()
 Harvest control rule to fish at some fraction of maximum sustainable yield

HCR_escapement()
 Fixed escapement harvest control rule

HCR_fixedF()
 Simple fixed F harvest control rule

HCR_segment()
 Segmented harvest control rules

HCR_ramp()
HCR40_10()
HCR60_20()
HCR80_40MSY()
 Linearly ramped harvest control rules

compare_models()
 Compare output from several assessment models

diagnostic()
diagnostic_AM()
 Diagnostic of assessments in MSE: did Assess models converge during MSE?

posterior()
RCMstan()
 Sample posterior of TMB models in SAMtool

prelim_AM()
 Preliminary Assessments in MSE

profile(<Assessment>)
profile(<RCModel>)
 Profile likelihood of assessment models

simulate()
 Generate simulated data from TMB models in SAMtool

retrospective()
 Retrospective analysis of assessment models

retrospective_AM()
 retrospective_AM (retrospective of Assessment model in MSE)

summary(<Assessment>)
 Summary of Assessment object

plot(<RCModel>,<missing>)
compare_RCM()
 Plot RCM scope output

plot(<Assessment>,<missing>)
plot(<Assessment>,<retro>)
 Plot Assessment object

plot(<prof>,<missing>)
 Plot profile object

plot(<retro>,<missing>)
summary(<retro>)
 Methods for retro object

plot_SR()
 Plot stockrecruitment function

plot_betavar()
 Plots a beta variable

plot_composition()
 Plot composition data

plot_lognormalvar()
 Plots a lognormal variable

plot_residuals()
 Plot residuals

plot_steepness()
 Plots probability distribution function of stockrecruit steepness

plot_timeseries()
 Plot time series of data
Data indicators
Calculate the statistical power of data indicators, generated in closedloop simulation, to detect differences between operating models (Carruthers and Hordyk 2018).

PRBcalc()
 Calculate mahalanobis distance (null and alternative MSEs) and statistical power for all MPs in an MSE

Probs()
 Calculates mahalanobis distance and rejection of the Null operating model

getinds()
 Characterize posterior predictive data

mahplot()
 Plot statistical power of the indicator with increasing time blocks

plot_crosscorr()
 Produce a crosscorrelation plot of the derived data arising from getinds(MSE_object)