Description Usage Arguments Details Value See Also Examples
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.
1 2 3 4 5 6 7 8 9 10 | 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
)
|
lens |
A vector containg the lengths of individual fish. |
alpha |
A numeric shape parameter to the beta distribution. See
|
beta |
A numeric shape parameter to the beta distribution. See
|
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 ( |
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. |
NEED DETAIL HERE.
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:
smpld a vector of logicals indicating whether each fish was sampled
(TRUE
) or not.
breaks the vector of length category breaks sent in breaks
.
probs the vector of capture probabilities that corresponds to the
length categories in breaks
. This vector may not equal the supplied
probs
vector if the user changed the capture probabilities with the
interactive graphic (i.e., using interact=TRUE
).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | ## 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)
|
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