Learn R Programming

DLMtool (version 4.4.1)

Data-class: Class 'Data'

Description

An object for storing data for analysis using data-limited methods

Arguments

Slots

Name

The name of the case-study

Year

A vector of years that correspond to catch and relative abundance data

Cat

Total annual catches

Ind

Relative abundance index

t

The number of years corresponding to AvC and Dt

AvC

Average catch over time t

Dt

Depletion over time t e.g. Bnow/Bthen

ML

Mean length time series

Mort

Natural mortality rate

FMSY_M

An assumed ratio of FMSY to M

BMSY_B0

The most productive stock size relative to unfished

L50

Length at 50 percent maturity

L95

Length at 95 percent maturity

Lbar

Mean length of catches over Lc (modal length)

Lc

Modal length

LFC

Length at first capture

LFS

smallest Length at full selection

CAA

Catch at Age data

Dep

Stock depletion Bnow/Bunfished (total stock)

Abun

An estimate of absolute current vulnerable abundance

SpAbun

An estimate of absolute current spawning stock abundance

vbK

The von Bertalanffy growth coefficient

vbLinf

Maximum length

vbt0

Theoretical age at length zero

LenCV

Coefficient of variation of length-at-age (assumed constant for all age classes)

wla

Weight-Length parameter alpha

wlb

Weight-Length parameter beta

steep

Steepness of the Beverton Holt stock-recruitment relationship

CV_Cat

Coefficient of variation in annual catches

CV_Dt

Coefficient of variation in depletion over time t

CV_AvC

Coefficient of variation in average catches over time t

CV_Ind

Coefficient of variation in the relative abundance index

CV_Mort

Coefficient of variation in natural mortality rate

CV_FMSY_M

Coefficient of variation in the ratio in FMSY/M

CV_BMSY_B0

Coefficient of variation in the position of the most productive stock size relative to unfished

CV_Dep

Coefficient of variation in current stock depletion

CV_Abun

Coefficient of variation in estimate of absolute current stock size

CV_vbK

Coefficient of variation in the von Bert. k parameter

CV_vbLinf

Coefficient of variation in maximum length

CV_vbt0

Coefficient of variation in age at length zero

CV_L50

Coefficient of variation in length at 50 per cent maturity

CV_LFC

Coefficient of variation in length at first capture

CV_LFS

Coefficient of variation in length at full selection

CV_wla

Coefficient of variation in weight-length parameter a

CV_wlb

Coefficient of variation in weight-length parameter b

CV_steep

Coefficient of variation in steepness

sigmaL

Assumed observaton error of the length composition data

MaxAge

Maximum age

Units

Units of the catch/absolute abundance estimates

Ref

A reference quota level

Ref_type

Its type

Log

A log of events

params

A place to store estimated parameters

PosMPs

The methods that can be applied to these data

MPs

The methods that were applied to these data

OM

A table of operating model conditions

Obs

A table of observation model conditions

TAC

The calculated TAC

TACbias

The known bias in the calculated TAC

Sense

The results of the sensitivity analysis

CAL_bins

The length bins for the catch-at-length data

CAL

Catch-at-length data

Cref

Reference or target catch level

Iref

Reference or target relative abundance index level

Bref

Reference or target biomass level

CV_Cref

CV for reference or target catch level

CV_Iref

CV for reference or target relative abundance index level

CV_Bref

CV for reference or target biomass level

CV_Rec

CV for recent recruitment strength

Rec

Recent recruitment strength

MPrec

The previous recommendation of a management proceedure

MPeff

The current level of effort

LHYear

The last historical year of the simulation (before projection)

nareas

Number of fishing areas

Misc

Optional list which is passed to MPs

Objects from the Class

Objects can be created by calls of the form new('Data', stock)

Examples

Run this code
# NOT RUN {
newdata<-new('Data')

# }

Run the code above in your browser using DataLab