#####################
## SolveIASA model ##
#####################
## Parameters and intial conditions.
pars.solve.iasa = c(
b1 = 21871, b2 = 4374,
df1 = 0.104, dm1 = 0.098, df2 = 0.125, dm2 = 0.118,
sf1 = 0.069, sf2 = 0.05, sm1 = 0.028, sm2 = 0.05,
k1 = 98050, k2 = 8055, h1 = 1, h2 = 0.5,
a = 0.054, alpha = 0.1, v = 0.2, z = 0.1)
init.solve.iasa = c(
f1 = 33425, fs1 = 10865,
m1 = 38039, ms1 = 6808,
f2 = 3343, fs2 = 109,
m2 = 3804, ms2 = 68)
# Solve for point estimates.
solve.iasa.pt <- SolveIASA(pars = pars.solve.iasa,
init = init.solve.iasa,
time = 0:15, method = 'rk4')
## Set ranges 10 % greater and lesser than the
## point estimates.
rg.solve.iasa <- SetRanges(pars = pars.solve.iasa)
## Calculate golobal sensitivity of combined parameters.
## To calculate global sensitivity to each parameter, set
## all as FALSE.
glob.all.solve.iasa <- CalculateGlobalSens(
model.out = solve.iasa.pt,
ranges = rg.solve.iasa,
sensv = 'n2', all = TRUE)
### Plot the sensitivities of combined parameters.
PlotGlobalSens(glob.all.solve.iasa)
Run the code above in your browser using DataLab