`lhPar.Rd`

Uses life history theory to derive parameters for biological relationships, i.e. or growth, maturity, natural mortality. Selectivity by default is set so age at peak selectivity is the same as age at 50% mature (a50) As a minimum all `lhPar` requires is `linf` the asymptotic length of the von Bertalannfy growth equation.

Uses life history theory to derive parameters for biological relationships, i.e. or growth, maturity, natural mortality. Selectivity by default is set so age at peak selectivity is the same as age at 50% mature (a50) As a minimum all `lhPar` requires is `linf` the asymptotic length of the von Bertalannfy growth equation.

```
lhPar(
...,
m = list(model = "gislason", params = c(m1 = 0.55, m2 = -1.61, m3 = 1.44)),
k = function(params, a = 3.15, b = -0.64) a * params["linf"]^b,
t0 = function(params, a = -0.3922, b = -0.2752, c = -1.038) -exp(a - b *
log(params$linf) %-% (c * log(params$k))),
l50 = function(params, a = 0.72, b = 0.93) a * params["linf"]^b
)
lhStk(
...,
k = function(params, a = 3.15, b = -0.64) a * params["linf"]^b,
t0 = function(params, a = -0.3922, b = -0.2752, c = -1.038) -exp(a - b *
log(params$linf) %-% (c * log(params$k))),
l50 = function(params, a = 0.72, b = 0.93) a * params["linf"]^b,
gowth = vonB,
mat = logistic,
sel = dnormal,
sr = "bevholt",
m = list(model = "gislason", params = c(m1 = 0.55, m2 = -1.61, m3 = 1.44)),
fmult = function(x) refpts(x)["msy", "harvest"] %*% FLQuant(seq(0, 2, length.out =
100)),
range = c(min = 0, max = 40, minfbar = 1, maxfbar = 40, plusgroup = 40),
spwn = 0,
fish = 0.5,
midyear = 0.5
)
```

- t0
of von Bertalanffy. This is a default that isnt normally derived from life history theory, as are the following args.

- sr
obsolete now replaced by sel3

- params
`FLPar`

object with parameters for life history equations and selection pattern. Need Linfinity to estimate other parameters, if any other parameters supplied in`code`

then these are not provided by the algorithm- a
coefficient of length weight relationship

- b
exponent of length weight relationship

- ato95
age at which 95% of fish are mature, offset to age at which 50% are mature

- s
steepness of stock recruitment relationship

- v
virgin biomass

- sel1
selectivity-at-age parameter for double normal, age at maximum selectivity by default set to same as age at 100% mature

- sel2
selectivity-at-age parameter for double normal, standard deviation of lefthand limb of double normal, by default 5

- sel3
selectivity-at-age parameter for double normal, standard deviation of righthand limb of double normal, by default 5000

- sl
obsolete now replaced by sel2

- m1
m-at-age parameter by default for Gislason empirical relationship

- m2
m-at-age parameter, by default for Gislason empirical relationship

- m3
m-at-age parameter, by default for Gislason empirical relationship

object of class `FLPar`

with missing parameters calculated from life history theory

object of class `FLPar`

with missing parameters calculated from life history theory

```
if (FALSE) {
#COMPARE with output of FLife::lhPar
x <- as(lhpar(linf=100), 'list')
x <- x[sort(names(x))]
y <- as(lhPar(FLPar(linf=100)), 'list')
y <- y[sort(names(y))]
all.equal(x,y)
for(i in seq(length(x)))
cat(names(x[i]), ":", unlist(x[i]), "-", names(y[i]), ":", unlist(y[i]), "\n")
# CALL with iters
lhpar(FLPar(linf=100), v=rnorm(100, 300, 200))
lhPar(FLPar(linf=rnorm(100, 80, 10)))
lhPar(FLPar(linf=100, v=rnorm(100, 300, 200)))
lhPar(FLPar(linf=100), FLPar(v=rnorm(100, 300, 200)))
lhPar(FLPar(linf=100, v=rnorm(100, 300, 200)), t0=-1, data.frame(a=1,b=7))
attributes(lhpar(FLPar(linf=100), v=rnorm(100, 300, 200)))$mmodel
}
if (FALSE) {
}
```