Package index • MSEtool Functions

Operating model

General functions

OM-class: Class 'OM'

OMdoc(): Generate OM Documentation Report

testOM: OM class objects

plot(<pars>) plot(<Stock>) plot(<Fleet>) plot(<Obs>) plot(<Imp>) plot(<Hist>) plot(<OM>): Plot Operating Model Object

Import

Convert stock assessment output, i.e., stock, fleet, and some observation error parameters, into an operating model

ASAP2OM() ASAP2Data(): Convert ASAP 3 assessments into an operating model

Assess2MOM(): Reads bootstrap estimates from a stock assessment model into a multi-fleet operating model.

Assess2OM() VPA2OM(): Reads bootstrap estimates from a stock assessment model (including VPA) into an operating model. Assess2OM is identical to VPA2OM.

Awatea2OM(): Reads MCMC estimates from Awatea (Paul Starr) processed r file structure into an operating model

BAM2MOM() BAM2OM(): Import a multi-stock, multi-fleet OM from a BAM object

iSCAM2OM() iSCAM2Data(): Reads MPD or MCMC estimates and data from iSCAM file structure into an operating model

SS2MOM() plot_SS2MOM() SS2OM() SSMOM2OM() plot_SS2OM() MOM_agg_fleets(): Import Stock Synthesis to MOM (2-sex multi-fleet) or OM (single-sex, single-fleet)

WHAM2OM(): Takes a fitted SAM model and samples historical population and fishing dynamics from the MLE fit and variance-covariance matrix.

Manual configuration

Manually parameterize the operating model

ChooseEffort() ChooseM() ChooseSelect(): Manually map parameters for the historical period of operating model

LH2OM() predictLH(): Predict missing life-history parameters

ML2D(): Depletion and F estimation from mean length of catches

SketchFun(): Manually map the historical relative fishing effort trajectory.

Turing() TuringMOM(): Turing Test

XL2Fleet(): Import Fleet Object from Excel file

XL2OM(): Load OM from Excel file

XL2Stock(): Import Stock Object from Excel file

makemov(): Calculates movement matrices from user inputs for fraction in each area (fracs) and probability of staying in areas (prob)

OM components

Stock

Object specifying biology and stock dynamics

Albacore Blue_shark Bluefin_tuna Bluefin_tuna_WAtl Butterfish Herring Mackerel Porgy Rockfish Snapper Sole Toothfish: Stock class objects

Stock-class: Class 'Stock'

Fleet

Object specifying fishing dynamics

DecE_Dom DecE_HDom DecE_NDom FlatE_Dom FlatE_HDom FlatE_NDom Generic_DecE Generic_FlatE Generic_Fleet Generic_IncE IncE_HDom IncE_NDom Low_Effort_Non_Target Target_All_Fish Targeting_Small_Fish: Fleet class objects

Fleet-class: Class 'Fleet'

Obs

Object specifying observation model (how data are simulated)

Generic_Obs Imprecise_Biased Imprecise_Unbiased Perfect_Info Precise_Biased Precise_Unbiased: Obs class objects

Obs-class: Class 'Obs'

Imp

Object specifying the extent of error in MP implementation

Overages Perfect_Imp: Imp class objects

Imp-class: Class 'Imp'

Hist

Object generated from the historical reconstruction of the system dynamics (output of runMSE(Hist = TRUE))

Hist-class: Class 'Hist'

Data objects

Includes functions to import and export Data objects, data frames describing slots, manipulate Data objects, and generate examples.

Atlantic_mackerel China_rockfish Cobia Example_datafile Gulf_blue_tilefish ourReefFish Red_snapper Simulation_1: Data class objects

Data-class: Class 'Data'

Data2csv(): Converts a Data object into a .csv data file

DataInit(): Initialize Data Input Files

DataSlots: DataSlots

Data_xl(): Read in Data object from Excel spreadsheet

Lag_Data(): Lag the time-series slots in a Data object by a specified number of time-steps

Report(): Generate a Data Report

SS2Data(): Reads data Stock Synthesis file structure into a Data object using package r4ss

SS2DataMOM(): Reads data Stock Synthesis file structure into a nested Data object analogous with multiMSE

XL2Data(): Import a Data object from Excel file

SimulatedData: SimulatedData Data

boxplot(<Data>): Boxplot of TAC recommendations

plot(<Data>): Plot Data object

plotOFL(): A generic OFL plot for NOAA use

summary(<Data>): Summary of Data object

select_MP(): Select DataList for an MP from MMSE@PPD

Management procedures

Calculate advice from management procedures

General

Can() Cant() DLMdiag() Needed(): Identify management procedures (MPs) based on data availability

Fease(): MP feasibility diagnostic

Input(): Function to run a set of input control methods

MPtype(): Management Procedure Type

RealFease(): MP feasibility diagnostic using real data

Required(): What management procedures need what data

Sense(): Sensitivity analysis

TAC(): Calculate TAC recommendations for more than one MP

TACfilter(): TAC Filter

tune_MP(): Tune MP

Uses(): Find the Management Procedures that use a particular data slot

runInMP(): Runs input control MPs on a Data object.

runMP(): Run a Management Procedure

Reference managment procedures

Management procedures reflecting idealized management, e.g., perfect knowledge of stock productivity, no fishing scenario, etc.

FMSYref() FMSYref50() FMSYref75() NFref() curEref(): Reference management procedures

Rec object

Output of management procedures to implement in the MSE simulation

Rec-class: Class 'Rec'

Run MSE simulation

runCOSEWIC() COSEWIC_Pplot() COSEWIC_Dplot() COSEWIC_Blow() COSEWIC_Hplot() COSEWIC_report() COSEWIC_tab() COSEWIC_tab_formatted(): COSEWIC MSE run using the correct MPs and projected time horizon

Simulate() Project() runMSE(): Run a Management Strategy Evaluation

setup(): Setup parallel processing

Evaluate MSE results

Performance metrics

PMobj-class: An object for storing data for analysis using data-limited methods

P10() P50() P100() PNOF() LTY() STY() Yield() PGK() AAVY() AAVE(): Performance Metrics Methods

General and diagnostic functions

MSE-class: Class 'MSE'

Converge(): Check Convergence

Dom(): Determine dominate MPs

VOI(): Calculate Value Of Information

VOI2(): Calculate Value Of Information 2

summary(<MSE>): Summary of MSE object

Plot MSE output (general)

Cplot(): Plot the median biomass and yield relative to last historical year

Kplot(): KOBE plot: a projection by projection plot of F/FMSY and B/BMSY

PMLimit() PMObj(): Create a table of Performance Limits and Performance Objectives

Pplot(): A projection by projection plot of F/FMSY and B/BMSY

Pplot2(): A projection by projection plot of F/FMSY, B/BMSY, B/B0, and yield

PWhisker(): Performance Whisker Plot

SSBrefplot(): Plot Spawning stock biomass and reference points for both historical and projected period

TradePlot() Tplot() Tplot2() Tplot3() NOAA_plot2(): Generic Trade-Plot Function

VOIplot(): Yet another Value of Information Plot

plot(<MSE>): Plot MSE object

wormplot(): Biomass wormplot

Plot MSE output (specific to management areas)

DFO_bar(): Department of Fisheries and Oceans stock status bar plot

DFO_hist(): Department of Fisheries and Oceans historical plot

DFO_plot(): Department of Fisheries and Oceans trade-off plot

DFO_plot2(): Department of Fisheries and Oceans default plot 2

DFO_quant(): Department of Fisheries and Oceans biomass quantile plot

DFO_proj(): Department of Fisheries and Oceans projection plot

DFO_report(): Create a standard DFO MSE report

DFO_spider(): DFO performance spider plot (top three MPs)

DFO_tab(): Create a standard DFO performance table

DFO_tab_formatted(): A formatted version of the standard DFO performance plot, color coded by thresholds

Cos_thresh_tab(): Current default thresholds for COSEWIC satisficing

Thresh_tab(): Current default thresholds for DFO satisficing

NOAA_plot(): National Oceanographic and Atmospheric Administration default plot 1

multiMSE

Multi-population (two-sex or multi-stock), multi-fleet operating models (class MOM) and corresponding MSE object (class MMSE)

Albacore_TwoFleet: MOM class objects

MOM-class: Class 'MOM'

MMSE-class: Class 'MMSE'

makeMOM(): Utility for making multi-OMs

makeRel() print(<Rel>) predict(<Rel>) simulate(<Rel>): MICE relationships for multi-OM

SimulateMOM() ProjectMOM() multiMSE(): Run a multi-fleet multi-stock Management Strategy Evaluation

multidebug(): A basic comparison of runMSE output (MSE) and multiMSE (MMSE)

plot(<MMSE>): Standard plot for an object of class MMSE (multi MSE)

plot(<MOM>,<missing>): Standard plot for an object of class MOM

plotRel(): Plot a relationship between stocks

plotmulti(): A basic SSB plot for debugging runMSE output

summary(<MMSE>): Summary of MMSE object

Miscellaneous

Convenient user functions to process various objects

avail(): What objects of this class are available

optCPU(): Determine optimal number of cpus

tinyErr(): Remove observation, implementation, and process error

writeCSV(): Internal function to write CSVs for objects

OM

CheckOM(): Check OM object is complete

Replace(): Replace an existing Stock, Fleet, Obs, or Imp object

MSEextra(): Load more data from MSEextra package

SubCpars(): Subset the cpars slot in an operating model

SubOM(): Subset a Stock, Fleet, Obs, or Imp object from an OM object

validcpars(): Valid custom parameters (cpars)

Data

CALsimp(): Simplifies the CAL slot of data object

CheckMPs(): Check that specified MPs are valid and will run on MSEtool::SimulatedData

replic8(): Enlarge (replicate) a DLM data object to create an additional dimension for simulation / sensitivity testing

MP

MPtype(): Management Procedure Type

CombineMMP(): Create a blank MP recommendations object (class Rec) of the right dimensions

MSE

Sub(): Subset MSE object by management procedure (MP) or simulation.

checkMSE() addMPs() joinMSE() joinHist() updateMSE(): Utility functions for MSE objects

joinData(): Join Data objects present in a list

Internal functions

Populations dynamics functions and other processing functions

MSYCalcs(): Internal function to calculate MSY Reference Points

applyMP(): Apply Management Procedures to an object of class Data

applyMMP(): Apply multi Management Procedures (class MMP) to a hierarchical list of Data class objects

calcRefYield(): Calculate Reference Yield

cparscheck(): Internal function for checking that the OM@cpars is formatted correctly

dnormal(): Double-normal selectivity curve

getmov2(): Optimization function to find a movement model that matches user specified movement characteristics modified for Rcpp.

getsel(): Calculate selectivity curve

hconv() R0conv() SRalphaconv() SRbetaconv(): Stock recruit parameterization

movestockCPP(): Apply the movement model to the stock for one time-step

simCAA(): Simulate Catch-at-Age Data

simCAL(): Simulate Catch-at-Length Data

simmov() plot_mov(): Calculates movement matrices from user inputs

Internal multiMSE

expandHerm() checkHerm() subsetHerm(): Internal Herm functions

multiData(): Combine data among fleets

multiDataS(): Combine data among stocks

Figures

join_plots(): Plot several plots with a shared legend

makeTransparent(): Make colors transparent

plotFun(): Print out plotting functions

plotquant(): A fairly tidy time-series quantile plot