Parameters | R Documentation |
A class that contains all model parameters
parameters(names = c(), vals = c(), transformed = TRUE,
base = new("Parameters"))
meanParameters(x)
## S3 method for class 'Parameters'
plot(x, xlim = c(0.001, 1), ...)
## S3 method for class 'Parameters'
lines(x, ...)
## S3 method for class 'Parameters'
as.list(x, ...)
## S3 method for class 'Parameters'
simulate(object, nsim = 1000, seed = NULL,
binsize = 5, keepZeros = TRUE, ...)
names |
String vector. Contains the names of the parameters that will have non default values. |
vals |
Numeric vector. The corresponding values, transformed if |
transformed |
Boolean. If TRUE vals should contain the transformed parameter values. |
base |
|
x |
a Parameters object |
xlim |
the x limits (x1, x2) of the plot. |
... |
Arguments passed to other methods. |
object |
a |
nsim |
number of individuals in the simulated sample |
seed |
the seed that is passed to |
binsize |
numeric, the width of the weight classes in grams |
keepZeros |
logical, if TRUE keep bins with zero frequency. Note that the zeros after the last non-zero bin are always droped. |
Returns an object of the Parameters class
logWinf
:Numeric scalar. Asymptotic weight
logFm
:Numeric scalar. Fishing mortality
logA
:Numeric scalar. Growth parameter
logn
:Numeric scalar. Exponent of consumption
logeta_F
:Numeric scalar. 50% retention size, relative to asymptotic weight
logeta_m
:Numeric scalar. 50% maturation size, relative to asymptotic weight
logeta_S
:Numeric scalar. 50% retention size (survey), relative to asymptotic weight
loga
:Numeric scalar. Physiological mortality
logepsilon_a
:Numeric scalar. Allocation to activity
logepsilon_r
:Numeric scalar. Recruitment efficiency
logWfs
:Numeric scalar. 50% retention size
logu
:Numeric scalar. Selectivity parameter, width o
M
:Numeric scalar. Number of internal weight classes
scaleWinf
:Numeric scalar. Scale of asymptotic weight
scaleFm
:Numeric scalar. Scale of fishing mortality
scaleA
:Numeric scalar. Scale of growth parameter
scalen
:Numeric scalar. Scale of exponent of consumption
scaleeta_F
:Numeric scalar. Scale of 50% retantion size
scaleeta_m
:Numeric scalar. Scale of 50% maturation size
scaleeta_S
:Numeric scalar. Scale of survey gear 50% retantion size
scalea
:Numeric scalar. Scale of the physiological mortality
scaleepsilon_a
:Numeric scalar. Scale of the allocation to activity
scaleepsilon_r
:Numeric scalar. Scale of recruitment efficiency
scaleWfs
:Numeric scalar. Scale of size of 50% retention
scaleu
:Numeric scalar.
Additional arguments are passed to plot.default
(from plot) and to lines
(from lines). From all other functions the extra arguments are ignored.
alko
alko
## Without any arguments gives a Parameters object with default values
parameters()
## Changing some parameters gives the corresponding object
par1 <- parameters(c("Winf", "Fm", "Wfs"), c(log(1000 / 10000), log(0.4 / 0.25), log(100 / 1000)))
par2 <- parameters(c("Winf", "Fm", "Wfs"), c(1000 , 0.4, 100), transformed=FALSE)
## Check if the two objects are equal
all.equal(par1, par2)
## Take a Parameters object and change one parameter
par <- parameters(c("Winf", "a", "Fm", "Wfs"), c(1000, 0.4, 0.2, 100), transformed = FALSE)
changeMatsize <- parameters("eta_m", 0.3, transformed =FALSE, base=par)
difference(par, changeMatsize)
## base comp difference percent.difference
## eta_m 0.25 0.3 -0.05 20
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.