Description Usage Arguments Details Value Note Author(s) References See Also Examples
Functions used as part of argument model to call simulation functions.
1 2 3 4 5 6 7 | logistic(t,p,x)
logistic.forced(t,p,x)
logistic.var(t,p,x)
logistic.z(t,p,x)
logistic.g(t,p,x,tz)
M3(t,p,x)
monod.batch(t,p,x)
|
t |
time |
p |
parameters, an array |
x |
state variable |
tz |
times of sudden disturbance |
State variable can be population density (logistic family), or chemical concentration (M3). Two states for monod.batch: chemical concentration and population density.
For logistic, p is dim 2: the intrinsic growth coeff, and the carrying capacity. For logistic.forced, p is dim 4: the intrinsic growth coeff, the carrying capacity, and disturbance parameters. For logistic.var, p is dim 5: mean of the intrinsic growth coeff, the carrying capacity, and, drift coeff, amplitude, and period of sinusoidal variation.
Functions logistic.z and logistic.g define discontinuous disturbance regime. Function logistic.z defines times of discontinuities, and logistic.g applies a linear disturbance at tz times defined by logistic.z.
For function M3, p is dim 2: half-rate concentration and maximum rate. For monod-batch p is dim 4: half-rate concentration, maximum rate, yield coefficient, and death rate.
Rate of change or derivative of model. Except logistic.z and logistic.g that return disturbance regime.
Model functions are employed mainly to define the ODE to be simulated by sim.comp, sim.mruns, sim.rnum, sim, simd and other simulation functions.
Nominal parameter values are defined in input files. Variation of param values are defined in lists.
Input files are in 'datafiles.zip' in directory 'datafiles' and organized by chapters of Acevedo (2012). Input files are required to run the examples below.
Miguel F. Acevedo Acevedo@unt.edu
Acevedo M.F. 2012. Simulation of Ecological and Environmental Models. CRC Press.
Hallam, T.G., 1986b. Population dynamics in a homogeneous environment. In Mathetmatical Ecology, eds. T. G. Hallam, and S. A. Levin, 61-94. New York: Springer-Verlag.
Hanson, F.B., and H.C. Tuckwell. 1981. Logistic growth with random density independent disasters. Theoretical Population Biology 19:1-18.
Simulation functions sim.comp
, sim.rnum
, sim.mruns
, sim
, simd
Methods euler
, RK4
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 | ## Not run:
# logistic
logis <- list(f=logistic)
# single run
t.X <- sim(logis,file="chp6/logistic-inp.csv")
# multiple runs
param <- list(plab="r", pval = seq(0.2,0.6,0.2))
t.X <- sim(logis,"chp6/logistic-inp.csv",param)
# Harvest, multiple runs
logis.f <- list(f=logistic.forced)
param <- list(plab="Ha",pval=c(0,-0.1,-0.2,-0.3))
t.X <- sim(logis.f,"chp7/logis-harvest-inp.csv",param)
# Seasonality
logis.v <- list(f=logistic.var)
param <- list(plab="Kd",pval=c(0,-0.5,-0.6))
t.X <- sim(logis.v,"chp7/logis-var-inp.csv",param)
# sudden disturbance
logis.sud <- list(f=logistic,z=logistic.z,g=logistic.g)
t.X <- simd(logis.sud,file="chp7/logis-sud-inp.csv")
# M3 decay multiple runs
m3decay<- list(f=M3)
param <- list(plab="Kmax", pval = seq(-20,-60,-10))
t.X <- sim(m3decay,"chp6/m3decay-inp.csv", param)
# monod batch multiple runs
monod <- list(f=monod.batch)
param <- list(plab="Kmax", pval = seq(0.5,1.5,0.5))
t.X <- sim(monod,"chp6/monod-batch-inp.csv", param)
## End(Not run)
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