Package 'LBSPR' reference manual

Title:	Length-Based Spawning Potential Ratio
Description:	Simulate expected equilibrium length composition, yield-per-recruit, and the spawning potential ratio (SPR) using the length-based SPR (LBSPR) model. Fit the LBSPR model to length data to estimate selectivity, relative apical fishing mortality, and the spawning potential ratio for data-limited fisheries. See Hordyk et al (2016) <doi:10.1139/cjfas-2015-0422> for more information about the LBSPR assessment method.
Authors:	Adrian Hordyk [aut, cre]
Maintainer:	Adrian Hordyk <[email protected]>
License:	GPL-3
Version:	0.1.9
Built:	2025-03-04 04:02:51 UTC
Source:	https://github.com/adrianhordyk/lbspr

Calculate Relative Yield, YPR, SPR, SSB, and Recruitment curves for F/M

Description

A function that takes a LB_pars or LB_obj object and returns a data frame of values for relative Yield, YPR, SPR, SSB, and Recruitment at different values of F/M

Usage

calcCurves(LB_obj)
calcCurves(LB_obj)

Arguments

LB_obj

An object of class 'LB_obj' or class 'LB_pars' that contains the life history and fishing information

Value

a dataframe with YPR, Yield, SSB, Rec, and FM

Author(s)

A. Hordyk

Report the location of the Data Files

Description

A function that returns the location of the example CSV files

Usage

DataDir()
DataDir()

Author(s)

A. Hordyk modified (i.e., stolen) from T. Carruthers' code (DLMtool package)

Kalman filter and Rauch-Tung-Striebel smoother

Description

A function that applies a filter and smoother to estimates

Usage

FilterSmooth(RawEsts, R = 1, Q = 0.1, Int = 100)
FilterSmooth(RawEsts, R = 1, Q = 0.1, Int = 100)

Arguments

`RawEsts`	a vector of estimated values
`R`	variance of sampling noise
`Q`	variance of random walk increments
`Int`	covariance of initial uncertainty

Value

a vector of smoothed values

Calculate F/M given SPR and other parameters

Description

A internal function that optimizes for F/M when SPR is provided in the simulation parameters.

Usage

getFMfun(FM, LB_pars, Control = list())
getFMfun(FM, LB_pars, Control = list())

Arguments

`FM`	a F/M value
`LB_pars`	an object of class `'LB_pars'` that contains the life history information
`Control`	a list of control options for the LBSPR model.

Details

The Control options are:

modtype: Model Type: either Growth-Type-Group Model (default: "GTG") or Age-Structured ("absel")
maxsd: Maximum number of standard deviations for length-at-age distribution (default is 2)
ngtg: Number of groups for the GTG model. Default is 13
P: Proportion of survival of initial cohort for maximum age for Age-Structured model. Default is 0.01
Nage: Number of pseudo-age classes in the Age Structured model. Default is 101
maxFM: Maximum value for F/M. Estimated values higher than this are trunctated to maxFM. Default is 4

Value

sum of squares value

Author(s)

A. Hordyk

Create a new LB_lengths object

Description

Function

Usage

## S4 method for signature 'LB_lengths'
initialize(
  .Object,
  file = "none",
  LB_pars = NULL,
  dataType = c("raw", "freq"),
  header = FALSE,
  verbose = TRUE,
  ...
)
## S4 method for signature 'LB_lengths'
initialize(
  .Object,
  file = "none",
  LB_pars = NULL,
  dataType = c("raw", "freq"),
  header = FALSE,
  verbose = TRUE,
  ...
)

Arguments

`.Object`	class of object to be created
`file`	file path and name to CSV containing parameters. Alternatively it can be a matrix or vector of length data
`LB_pars`	a object of class LB_pars
`dataType`	is the length data individual measurements (raw) or a length frequency (freq)?
`header`	is there a header?
`verbose`	display a message?
`...`	optional additional arguments passed to read.csv

Value

a object of class 'LB_lengths'

Author(s)

A. Hordyk

An S4 class containing length data

Description

An S4 class containing length data

Slots

LMids: A numeric vector containing the mid-points of the length bins
LData: A numeric matrix containing length data
L_units: Character descrbing units of the length measurements
Years: A numeric vector containing the year indices
NYears: A length-one numeric vector for number of years
Elog: A error log

An S4 class containing all parameters for the LBSPR model

Description

An S4 class containing all parameters for the LBSPR model

Slots

SPR: The Spawning Potential Ratio
Yield: Relative yield
YPR: Yield per recruit
SSB: Spawning stock biomass (relative only)
SSB0: Unfished spawning stock biomass
B0: Unfished biomass
LMids: A numeric vector containing the mid-points of the length bins
pLCatch: A numeric vector containg expected proportion for each length class in the catch
pLPop: A numeric vector containg expected proportion for each length class in the population
RelRec: Relative recruitment
Ests: A matrix of estimated values
Vars: A vector of estimated variance for SL50, SL95, F/M and SPR
NLL: A numeric NLL values
maxFM: A numeric of maximum estimated F/M value (note this is apical F)
SPRatsize: A vector of cumulative SPR at length (currently only works for GTG model)
fitLog: A vector of error logs for each fit. 0 means everything is okay.

An S4 class containing life history and other parameters

Description

An S4 class containing life history and other parameters

Slots

Species: Character vector of species name
MK: A length-one numeric vector for M/K ratio
M: An optional value for natural mortality (M)
Linf: A length-one numeric vector for Linf
L_units: Character describing units of length parameters
CVLinf: A length-one numeric vector for CV of length-at-age
L50: A length-one numeric vector for length at 50% maturity
L95: A length-one numeric vector for length at 95% maturity
Walpha: A length-one numeric vector for alpha parameter of length-weight relationship
Walpha_units: Character describing units for weight scaling parameter
Wbeta: A length-one numeric vector for beta parameter of length-weight relationship
FecB: A length-one numeric vector for beta parameter of length-fecundity relationship
Steepness: A length-one numeric vector for steepness of SRR
Mpow: A length-one numeric vector for M at length
R0: A length-one numeric vector for initial number of recruits (1 for per-recruit)
SL50: A length-one numeric vector for length at 50% selectivity
SL95: A length-one numeric vector for length at 95% selectivity
MLL: Minimum legal length (inflection point)
sdLegal: Standard deviation of MLL curve
fDisc: Fraction discarded that die
FM: A length-one numeric vector for F/M ratio (note this is apical F)
SPR: A length-one numeric vector for SPR
BinMin: A length-one numeric vector for minimum length bin
BinMax: A length-one numeric vector for maximum length bin
BinWidth: A length-one numeric vector for width of length bins

LBSPR Optimization function for age-based selectivity model

Description

Internal optimization function

Usage

LBSPR_NLLabsel(
  starts,
  x,
  P,
  LMids,
  LBins,
  LDat,
  MK,
  Linf,
  FecB,
  L50,
  L95,
  maxsd,
  CVLinf,
  Nage,
  usePen
)
LBSPR_NLLabsel(
  starts,
  x,
  P,
  LMids,
  LBins,
  LDat,
  MK,
  Linf,
  FecB,
  L50,
  L95,
  maxsd,
  CVLinf,
  Nage,
  usePen
)

Arguments

`starts`	a vector of starting parameters, relative SL50 (SL50/Linf), deltaSL (SL95-SL50)/Linf, and F/M (in log space)
`x`	vector of relative ages
`P`	numeric value indicating proportion of cohort remaining at maximum age
`LMids`	a vector of the midpoints of the length classes
`LBins`	a vector of length classes
`LDat`	a vector of lenght frequencies. Must be same length as LMids
`MK`	the M/K value
`Linf`	the Linf value for the population as a hole
`FecB`	exponent of the length-fecundity relationship
`L50`	length at 50 per cent maturity
`L95`	length at 95 per cent maturity
`maxsd`	numeric value - maximum number of standard deviations of length-at-age dist
`CVLinf`	CV of length-at-age
`Nage`	number of pseudo age-classes
`usePen`	logical to use penalty for extreme estimates of selectivity

Value

negative log-likelihood value

Author(s)

A. Hordyk

LBSPR Optimization function for GTG model

Description

Internal optimization function

Usage

LBSPR_NLLgtg(
  starts,
  LMids,
  LBins,
  LDat,
  gtgLinfs,
  MKMat,
  MK,
  Linf,
  ngtg,
  recP,
  usePen
)
LBSPR_NLLgtg(
  starts,
  LMids,
  LBins,
  LDat,
  gtgLinfs,
  MKMat,
  MK,
  Linf,
  ngtg,
  recP,
  usePen
)

Arguments

`starts`	a vector of starting parameters, relative SL50 (SL50/Linf), deltaSL (SL95-SL50)/Linf, and F/M (in log space)
`LMids`	a vector of the midpoints of the length classes
`LBins`	a vector of length classes
`LDat`	a vector of lenght frequencies. Must be same length as LMids
`gtgLinfs`	a vector of Linfs for the growth-type-groups
`MKMat`	a matrix of M/K for each GTG and length-class
`MK`	the M/K value
`Linf`	the Linf value for the population as a hole
`ngtg`	the number of growth-type-groups
`recP`	a vector of recruitment by GTG
`usePen`	logical to use penalty for extreme estimates of selectivity

Value

negative log-likelihood value

Author(s)

A. Hordyk

Fit LBSPR model to length data

Description

A function that fits the LBSPR model to length data

Usage

LBSPRfit(
  LB_pars = NULL,
  LB_lengths = NULL,
  yrs = NA,
  Control = list(),
  pen = TRUE,
  verbose = TRUE,
  useCPP = TRUE,
  ...
)
LBSPRfit(
  LB_pars = NULL,
  LB_lengths = NULL,
  yrs = NA,
  Control = list(),
  pen = TRUE,
  verbose = TRUE,
  useCPP = TRUE,
  ...
)

Arguments

`LB_pars`	an object of class `'LB_pars'` that contains the life history information
`LB_lengths`	an object of class `'LB_lengths'` that contains the length data
`yrs`	index of years to include. If NA the model is run on all years
`Control`	a list of control options for the LBSPR model.
`pen`	apply a penalty if estimate of selectivity is very high?
`verbose`	display messages?
`useCPP`	use cpp optimization code?
`...`	additional parameters to pass to `FilterSmooth`

Details

The Control options are:

modtype: Model Type: either Growth-Type-Group Model (default: "GTG") or Age-Structured ("absel")
maxsd: Maximum number of standard deviations for length-at-age distribution (default is 2)
ngtg: Number of groups for the GTG model. Default is 13
P: Proportion of survival of initial cohort for maximum age for Age-Structured model. Default is 0.01
Nage: Number of pseudo-age classes in the Age Structured model. Default is 101
maxFM: Maximum value for F/M. Estimated values higher than this are trunctated to maxFM. Default is 4

Value

a object of class 'LB_obj'

Author(s)

A. Hordyk

Examples

## Not run: 
MyFit <- LBSPRfit(LBparameters, LBlengths)
MyFit@Ests

## End(Not run)

## Not run: 
MyFit <- LBSPRfit(LBparameters, LBlengths)
MyFit@Ests

## End(Not run)

Internal function to fit LBSPR model to length data

Description

An internal function that fits the LBSPR model to a single year of length data

Usage

LBSPRfit_(
  yr = 1,
  LB_pars = NULL,
  LB_lengths = NULL,
  Control = list(),
  pen = TRUE,
  useCPP = TRUE,
  verbose = TRUE
)
LBSPRfit_(
  yr = 1,
  LB_pars = NULL,
  LB_lengths = NULL,
  Control = list(),
  pen = TRUE,
  useCPP = TRUE,
  verbose = TRUE
)

Arguments

`yr`	index of the year column to fit model to
`LB_pars`	an object of class `'LB_pars'` that contains the life history information
`LB_lengths`	an object of class `'LB_lengths'` that contains the length data
`Control`	a list of control options for the LBSPR model.
`pen`	apply a penalty if estimate of selectivity is very high?
`useCPP`	use cpp optimization code?
`verbose`	display messages?

Details

The Control options are:

modtype: Model Type: either Growth-Type-Group Model (default: "GTG") or Age-Structured ("absel")
maxsd: Maximum number of standard deviations for length-at-age distribution (default is 2)
ngtg: Number of groups for the GTG model. Default is 13
P: Proportion of survival of initial cohort for maximum age for Age-Structured model. Default is 0.01
Nage: Number of pseudo-age classes in the Age Structured model. Default is 101
maxFM: Maximum value for F/M. Estimated values higher than this are trunctated to maxFM. Default is 4

Value

a object of class 'LB_obj'

Author(s)

A. Hordyk

Optimisation Routine for fitting LBSPR

Description

A function that calculate the negative log-likelihood of the LBSPR model

Usage

LBSPRopt(
  trypars,
  yr = 1,
  LB_pars = NULL,
  LB_lengths = NULL,
  Control = list(),
  pen = TRUE
)
LBSPRopt(
  trypars,
  yr = 1,
  LB_pars = NULL,
  LB_lengths = NULL,
  Control = list(),
  pen = TRUE
)

Arguments

`trypars`	a vector of exploitation parameters in log space
`yr`	index of the year column to fit the model to
`LB_pars`	an object of class `'LB_pars'` that contains the life history information
`LB_lengths`	an object of class `'LB_lengths'` that contains the length data
`Control`	a list of control options for the LBSPR model.
`pen`	apply a penalty if estimate of selectivity is very high?

Details

The Control options are:

modtype: Model Type: either Growth-Type-Group Model (default: "GTG") or Age-Structured ("absel")
maxsd: Maximum number of standard deviations for length-at-age distribution (default is 2)
ngtg: Number of groups for the GTG model. Default is 13
P: Proportion of survival of initial cohort for maximum age for Age-Structured model. Default is 0.01
Nage: Number of pseudo-age classes in the Age Structured model. Default is 101
maxFM: Maximum value for F/M. Estimated values higher than this are trunctated to maxFM. Default is 4

Value

a NLL value

Author(s)

A. Hordyk

LBSPR Simulation Model

Description

Function that generates the expected equilbrium size composition given biological parameters, and fishing mortality and selectivity pattern.

Usage

LBSPRsim(LB_pars = NULL, Control = list(), verbose = TRUE)
LBSPRsim(LB_pars = NULL, Control = list(), verbose = TRUE)

Arguments

`LB_pars`	an object of class `'LB_pars'` that contains the life history information
`Control`	a list of control options for the LBSPR model.
`verbose`	display messages?

Details

The Control options are:

modtype: Model Type: either Growth-Type-Group Model (default: "GTG") or Age-Structured ("absel")
maxsd: Maximum number of standard deviations for length-at-age distribution (default is 2)
ngtg: Number of groups for the GTG model. Default is 13
P: Proportion of survival of initial cohort for maximum age for Age-Structured model. Default is 0.01
Nage: Number of pseudo-age classes in the Age Structured model. Default is 101
maxFM: Maximum value for F/M. Estimated values higher than this are trunctated to maxFM. Default is 4

Value

a object of class 'LB_obj'

Author(s)

A. Hordyk

Examples

 LB_pars <- new("LB_pars")
 LB_pars@MK <- 1.5
 LB_pars@Linf <- 100
 LB_pars@L50 <- 50
 LB_pars@L95 <- 55
 LB_pars@SL50 <- 60
 LB_pars@SL95 <- 65
 LB_pars@FM <- 1
 Sim <- LBSPRsim(LB_pars)
 Sim@SPR

LB_pars <- new("LB_pars")
 LB_pars@MK <- 1.5
 LB_pars@Linf <- 100
 LB_pars@L50 <- 50
 LB_pars@L95 <- 55
 LB_pars@SL50 <- 60
 LB_pars@SL95 <- 65
 LB_pars@FM <- 1
 Sim <- LBSPRsim(LB_pars)
 Sim@SPR

Internal LBSPR Simulation Model

Description

A internal function that generates the expected equilbrium size composition given biological parameters, and fishing mortality and selectivity pattern. Typically only used by other functions in the package.

Usage

LBSPRsim_(LB_pars = NULL, Control = list(), verbose = TRUE, doCheck = TRUE)
LBSPRsim_(LB_pars = NULL, Control = list(), verbose = TRUE, doCheck = TRUE)

Arguments

`LB_pars`	an object of class `'LB_pars'` that contains the life history information
`Control`	a list of control options for the LBSPR model.
`verbose`	display messages?
`doCheck`	check if the LB_pars object is valid? Switch off when calling function from a optimization routine.

Details

The Control options are:

modtype: Model Type: either Growth-Type-Group Model (default: "GTG") or Age-Structured ("absel")
maxsd: Maximum number of standard deviations for length-at-age distribution (default is 2)
ngtg: Number of groups for the GTG model. Default is 13
P: Proportion of survival of initial cohort for maximum age for Age-Structured model. Default is 0.01
Nage: Number of pseudo-age classes in the Age Structured model. Default is 101
maxFM: Maximum value for F/M. Estimated values higher than this are trunctated to maxFM. Default is 4

Value

a object of class 'LB_obj'

Author(s)

A. Hordyk

Plot the Relative Yield, YPR, SPR, SSB, and Recruitment curves

Description

A function that plots the Relative Yield, YPR, SPR, SSB, and Recruitment curves

Usage

plotCurves(
  LB_obj,
  X = c("FM", "SSB", "SPR"),
  Y = c("SPR", "SSB", "Yield"),
  size.axtex = 12,
  size.title = 14,
  size.leg = 12,
  size.pt = 4,
  inc.pts = TRUE
)
plotCurves(
  LB_obj,
  X = c("FM", "SSB", "SPR"),
  Y = c("SPR", "SSB", "Yield"),
  size.axtex = 12,
  size.title = 14,
  size.leg = 12,
  size.pt = 4,
  inc.pts = TRUE
)

Arguments

`LB_obj`	An object of class `'LB_obj'` that contains the life history and fishing information
`X`	a character value indicating what to plot on the x-axis: F/M (`"FM"`) or SSB (`"SSB"`)
`Y`	a character value indicating what to plot on the y-axis: `SPR`, `SSB`, `Yield`, `YPR` or `Rec`(multiple okay)
`size.axtex`	size of the axis text
`size.title`	size of axis title
`size.leg`	size of legend text
`size.pt`	size of the points on the plots
`inc.pts`	Include points on the plots?

Value

a ggplot object

Author(s)

A. Hordyk

Plot LBSPR model estimates

Description

A function that plots the estimates of the LBSPR with a smoother line

Usage

plotEsts(
  LB_obj = NULL,
  pars = c("Sel", "FM", "SPR"),
  Lwd = 2.5,
  ptCex = 1.25,
  axCex = 1.45,
  labCex = 1.55,
  doSmooth = TRUE,
  incL50 = FALSE,
  CIcol = "darkgray",
  L50col = "gray"
)
plotEsts(
  LB_obj = NULL,
  pars = c("Sel", "FM", "SPR"),
  Lwd = 2.5,
  ptCex = 1.25,
  axCex = 1.45,
  labCex = 1.55,
  doSmooth = TRUE,
  incL50 = FALSE,
  CIcol = "darkgray",
  L50col = "gray"
)

Arguments

`LB_obj`	an object of class `'LB_obj'` that contains the life history and fishing information
`pars`	a character vectors specifying which plots to create
`Lwd`	line width
`ptCex`	size of plotted points
`axCex`	size of the axis
`labCex`	size of axis label
`doSmooth`	apply the smoother?
`incL50`	include L50 line?
`CIcol`	colour of the confidence interval bars
`L50col`	colour of L50 line (if included)

Author(s)

A. Hordyk

Plot the maturity-at-length and selectivity-at-length curves

Description

A function that plots the maturity-at-length and selectivity-at-length curves

Usage

plotMat(
  LB_obj = NULL,
  size.axtex = 12,
  size.title = 14,
  size.leg = 12,
  useSmooth = TRUE,
  Title = NULL
)
plotMat(
  LB_obj = NULL,
  size.axtex = 12,
  size.title = 14,
  size.leg = 12,
  useSmooth = TRUE,
  Title = NULL
)

Arguments

`LB_obj`	an object of class `'LB_obj'` that contains the life history and fishing information
`size.axtex`	size of the axis text
`size.title`	size of axis title
`size.leg`	size of legend text
`useSmooth`	use the smoothed estimates?
`Title`	optional character string for plot title

Value

a ggplot object

Author(s)

A. Hordyk

General plotting function for simulated data

Description

A general function that plots the simulation object. Includes four different plots: equilbrium size structure, maturity and selectivity curves, growth curves, and relative Yield, YPR, SPR, SSB, and Recruitment curves.

Usage

plotSim(
  LB_obj = NULL,
  type = c("all", "len.freq", "growth", "maturity.select", "yield.curve"),
  lf.type = c("catch", "pop"),
  growth.type = c("LAA", "WAA"),
  y.type = c("SPR", "SSB", "Yield", "YPR"),
  x.type = c("FM", "SSB", "SPR"),
  perRec = FALSE,
  inc.SPR = TRUE,
  Cols = NULL,
  size.axtex = 12,
  size.title = 14,
  size.SPR = 4,
  size.leg = 12,
  inc.pts = TRUE,
  size.pt = 4
)
plotSim(
  LB_obj = NULL,
  type = c("all", "len.freq", "growth", "maturity.select", "yield.curve"),
  lf.type = c("catch", "pop"),
  growth.type = c("LAA", "WAA"),
  y.type = c("SPR", "SSB", "Yield", "YPR"),
  x.type = c("FM", "SSB", "SPR"),
  perRec = FALSE,
  inc.SPR = TRUE,
  Cols = NULL,
  size.axtex = 12,
  size.title = 14,
  size.SPR = 4,
  size.leg = 12,
  inc.pts = TRUE,
  size.pt = 4
)

Arguments

`LB_obj`	an object of class `'LB_obj'` that contains the life history and fishing information
`type`	a character value indicating which plots to include: "all", "len.freq", "growth", "maturity.select", "yield.curve"
`lf.type`	a character value indicating if the `catch` or `pop` (population) should be plotted for the length frequency
`growth.type`	should growth be plotted as length-at-age (`"LAA"`) or weight-at-age (`"WAA"`)
`y.type`	what curves should be plotted on y-axis? `"SPR"`, `"SSB"`, `"Yield"`, `"YPR"`
`x.type`	what curves should be plotted on x-axis? `"FM"`, `"SSB"`, `"SPR"`
`perRec`	a logical to indicate if plot should be per-recruit (ignore steepness) or not (zero recruitment if SPR below replacement level)
`inc.SPR`	a logical to indicate if SPR value should be printed in top right corner of plot
`Cols`	optional character vector of colours for the plot
`size.axtex`	size of the axis text
`size.title`	size of axis title
`size.SPR`	size of SPR text
`size.leg`	size of legend text
`inc.pts`	Include points on the plots?
`size.pt`	size of the points on the plots

Value

a ggplot object

Author(s)

A. Hordyk

Examples

 LB_pars <- new("LB_pars")
 LB_pars@MK <- 1.5
 LB_pars@Linf <- 100
 LB_pars@L50 <- 50
 LB_pars@L95 <- 55
 LB_pars@SL50 <- 60
 LB_pars@SL95 <- 65
 LB_pars@FM <- 1
 Sim <- LBSPRsim(LB_pars)
 plotSim(Sim)

LB_pars <- new("LB_pars")
 LB_pars@MK <- 1.5
 LB_pars@Linf <- 100
 LB_pars@L50 <- 50
 LB_pars@L95 <- 55
 LB_pars@SL50 <- 60
 LB_pars@SL95 <- 65
 LB_pars@FM <- 1
 Sim <- LBSPRsim(LB_pars)
 plotSim(Sim)

Plot the size data and model fits

Description

A function that plots size data and the fitted LBSPR model

Usage

plotSize(
  LB_obj = NULL,
  size.axtex = 12,
  size.title = 14,
  Title = NULL,
  scales = c("fixed", "free_x", "free_y", "free"),
  inc.text = FALSE,
  warn.size = 0.8
)
plotSize(
  LB_obj = NULL,
  size.axtex = 12,
  size.title = 14,
  Title = NULL,
  scales = c("fixed", "free_x", "free_y", "free"),
  inc.text = FALSE,
  warn.size = 0.8
)

Arguments

`LB_obj`	an object of class `'LB_obj'` that contains the life history and fishing information
`size.axtex`	size of the axis text
`size.title`	size of axis title
`Title`	optional character string for plot title
`scales`	argument to ggplot2 function. Are scales shared across all facets (the default, "fixed"), or do they vary across rows ("free_x"), columns ("free_y"), or both rows and columns ("free")
`inc.text`	Include text on plotting warning of high F or selectivity estimates?
`warn.size`	numeric. Size of font for the warnings

Value

a ggplot object

Author(s)

A. Hordyk

Circle of estimated SPR and target and limit points

Description

A function that creates a circle plot showing the estimated SPR relative to the target and limit reference points

Usage

plotSPRCirc(
  LB_obj = NULL,
  SPRTarg = 0.4,
  SPRLim = 0.2,
  useSmooth = TRUE,
  Title = FALSE,
  Leg = TRUE,
  limcol = "#ff1919",
  targcol = "#f2ff02",
  abtgcol = "#32ff36",
  labcol = NULL,
  bgcol = "#FAFAFA",
  labcex = 2,
  texcex = 1.3
)
plotSPRCirc(
  LB_obj = NULL,
  SPRTarg = 0.4,
  SPRLim = 0.2,
  useSmooth = TRUE,
  Title = FALSE,
  Leg = TRUE,
  limcol = "#ff1919",
  targcol = "#f2ff02",
  abtgcol = "#32ff36",
  labcol = NULL,
  bgcol = "#FAFAFA",
  labcex = 2,
  texcex = 1.3
)

Arguments

`LB_obj`	an object of class `'LB_obj'` that contains the life history and fishing information
`SPRTarg`	a numeric value specifying the SPR target
`SPRLim`	a numeric value specifying the SPR limit
`useSmooth`	use the smoothed estimates? Usually would want to do this
`Title`	include the title?
`Leg`	include the legend?
`limcol`	colour for SPR Limit (hex; default is red)
`targcol`	colour for SPR target (hex; default is yellow)
`abtgcol`	colour for above SPR target (hex; default is green)
`labcol`	optional fixed colour for estimated SPR label
`bgcol`	colour for the background
`labcex`	size for the estimated SPR label
`texcex`	size for estimated other labels

Author(s)

A. Hordyk

Plot sampled length structure against target simulated size composition

Description

A function that plots the observed size structure against the expected size composition at the target SPR

Usage

plotTarg(
  LB_pars = NULL,
  LB_lengths = NULL,
  yr = 1,
  Cols = NULL,
  title = NULL,
  targtext = TRUE,
  size.axtex = 12,
  size.title = 14,
  scales = c("fixed", "free_x", "free_y", "free")
)
plotTarg(
  LB_pars = NULL,
  LB_lengths = NULL,
  yr = 1,
  Cols = NULL,
  title = NULL,
  targtext = TRUE,
  size.axtex = 12,
  size.title = 14,
  scales = c("fixed", "free_x", "free_y", "free")
)

Arguments

`LB_pars`	an object of class `'LB_pars'` that contains the life history and fishing information
`LB_lengths`	an object of class `'LB_lengths'` that contains the observed size data
`yr`	index for sampled length data (defaults to 1)
`Cols`	optional character vector of colours for the plot
`title`	character - optional title for plot
`targtext`	logical - should the SPR target text be displayed as a subtitle?
`size.axtex`	size of the axis text
`size.title`	size of axis title
`scales`	argument to ggplot2 function. Are scales shared across all facets (the default, "fixed"), or do they vary across rows ("free_x"), columns ("free_y"), or both rows and columns ("free")

Value

a ggplot object

Author(s)

A. Hordyk

Run a Shiny Application

Description

Shiny runs one of the Shiny Applications that are included in the package

Usage

Shiny(app)
Shiny(app)

Arguments

app

The name of the Shiny application to run. Currently the available Shiny apps are "LBSPR" and "Sim"

References

Modified from Deal Attali's code: https://deanattali.com/2015/04/21/r-package-shiny-app/

`.Object`	class of object to be created
`defaults`	use defaults?
`verbose`	display a message?

Package 'LBSPR'

Help Index

Calculate Relative Yield, YPR, SPR, SSB, and Recruitment curves for F/M

Description

Usage

Arguments

Value

Author(s)

Report the location of the Data Files

Description

Usage

Author(s)

Kalman filter and Rauch-Tung-Striebel smoother

Description

Usage

Arguments

Value

Calculate F/M given SPR and other parameters

Description

Usage

Arguments

Details

Value

Author(s)

Create a new LB_lengths object

Description

Usage

Arguments

Value

Author(s)

Create a new LB_obj object

Description

Usage

Arguments

Value

Author(s)

Create a new LB_pars object

Description

Usage

Arguments

Value

Author(s)

An S4 class containing length data

Description

Slots

An S4 class containing all parameters for the LBSPR model

Description

Slots

An S4 class containing life history and other parameters

Description

Slots

LBSPR Optimization function for age-based selectivity model

Description

Usage

Arguments

Value

Author(s)

LBSPR Optimization function for GTG model

Description

Usage

Arguments

Value

Author(s)

Fit LBSPR model to length data

Description

Usage

Arguments

Details

Value

Author(s)

Examples

Internal function to fit LBSPR model to length data

Description

Usage

Arguments

Details

Value

Author(s)

Optimisation Routine for fitting LBSPR

Description