mgi: Mean growth increment

In ejosymart/Gtransition: Estimate a Stochastic Growth Matrix Based on Length Structure Data

Mean growth increment

Description

Estimate mean growth increment \bar Δ_l for the individuals in length class l.

Usage

mgi(lowerL, upperL, classL, Linf, k, gm = 1, dl = 0.1, method = "vonB")

Arguments

lowerL	a numeric value that represents the smallest observed size.
upperL	a numeric value that represents the highest observed size.
classL	a numeric value that represents the range length classes.
Linf	a numeric value that represents the theoretical asymptotic length of an individual L_∞.
k	a numeric value that represents the growth rate parameter.
gm	a numeric value that represents the incremental relative rate of relative growth rate. Required when "Schnute" method is selected.
dl	a numeric value represents a constant relative rate of relative growth rate. Required when "Schnute" method is selected.
method	a character string defining the growth equation to be used. One of "vonB" (default), "Gompertz", "Logistic" or "Schunute".

Details

Estimate mean growth increment.

Value

A list of class 'Gincrement'.

delta the mean growth increment.

Laverage he midlength of the length class l.

References

Sullivan P.J., Lai H., Galluci V.F. (1990). A Catch-at-Length analysis that incorporates a stochastic model of growth. Can. J. Fish. Aquat. Sci. 47: 184-198.

Examples

output <- mgi(lowerL = 78, upperL = 202, classL = 4, Linf = 197.42, k = 0.1938, method = "vonB")

output
output$delta
output$Laverage

ejosymart/Gtransition documentation built on Feb. 11, 2023, 2:29 a.m.