simLenSelectP {FSATeach}R Documentation

Simulate sampling fish based on length selectivity.

Description

Constructs a sample of fish based on a user-supplied length-based selectivity curve. The selectivity curve can be supplied via a parametric model (the beta distribution) or manually for various length categories.

Usage

  simLenSelectP(lens, alpha = 1, beta = 1, max.height = 1,
    show = FALSE)

  simLenSelectM(lens, breaks,
    probs = rep(max.height, length(breaks)),
    max.height = 1, interact = TRUE, digits = 2)

Arguments

lens

A vector containg the lengths of individual fish.

alpha

A numeric shape parameter to the beta distribution. See dbeta.

beta

A numeric shape parameter to the beta distribution. See dbeta.

max.height

A numeric that controls the maximum height of the probability distribution – i.e., this will be the maximum probability of capture.

show

A logical indicating whether a graphic of the selectivity curve should be shown (=TRUE) or not (=TRUE; default).

breaks

A numeric vector of lower values for the break points of the length categories.

probs

A numeric vector of capture probabilities (i.e., selectivities) for each length category. Default is a vector containing all ones – i.e., no selectivity by length category.

interact

A logical indicating whether the capture probabilities (i.e., selectivities) should be chosen by the user interacting with a selectivity plot. See details.

digits

A numeric indicating the number of digits that should be used when selecting the capture probabilities. Smaller values represent coarser choices.

Details

NEED DETAIL HERE.

Value

If simLenSelectP is used then a vector of logicals indicating whether each fish was sampled (TRUE) or not. If simLenSelectM is used then a list that contains the following three items is returned:

See Also

simAges, simLenFromAge

Examples

## Load FSA package for Summarize()
library(FSA)

## set seed for repeatability
set.seed(5234734)

## Simulated individual ages (random)
#    see simAges functions
bg.ages <- simAges(N0=500,A=0.35)

## Simulated lengths, given the above ages
bg.lens <- simLenFromAge(bg.ages,228,0.206,0,8)

## Simulated samplings given the above lengths and
##   selectivities from a beta(3,5)
bg.smpl <- simLenSelectP(bg.lens,3,5)
# append ages, lengths, and samplings into one data frame
bg.df1 <- data.frame(age=bg.ages,len=bg.lens,smpld=bg.smpl)
# get only those that were sampled
bg.df1a <- Subset(bg.df1,smpld)
# Summaries
Summarize(len~age,data=bg.df1,digits=1)
Summarize(len~age,data=bg.df1a,digits=1)

## Simulated samplings given the above lengths and user supplied selectivities
bg.brks <- seq(20,230,10)
bg.prbs1 <- c(0.0,0.0,0.0,0.1,0.3,0.6,0.9,0.9,1.0,1.0,1.0,1.0,1.0,1.0,1.0,0.9,
 0.8,0.6,0.3,0.2,0.1,0.0)
bg.smpl1 <- simLenSelectM(bg.lens,bg.brks,bg.prbs1,interact=FALSE)
bg.df2 <- data.frame(age=bg.ages,len=bg.lens,smpld=bg.smpl1$smpld)
bg.df2a <- Subset(bg.df2,smpld)
Summarize(len~age,data=bg.df2,digits=1)
Summarize(len~age,data=bg.df2a,digits=1)

## Simulated samplings given the above lengths and selectivities from interactive choices
#  NOT RUN because of interactive choices
## Not run: 
bg.brks <- seq(20,230,10)
bg.smpl2 <- simLenSelectM(bg.lens,bg.brks)
bg.df3 <- data.frame(age=bg.ages,len=bg.lens,smpld=bg.smpl2$smpld)
bg.df3a <- Subset(bg.df3,smpld)
Summarize(len~age,data=bg.df3,digits=1)
Summarize(len~age,data=bg.df3a,digits=1)

## End(Not run)

[Package FSATeach version 0.0.1 Index]