Description Usage Arguments Value See Also Examples
Interface of optimization functions for double logistics and other parametric curve fitting functions.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | optim_pheno(
prior,
sFUN,
y,
t,
tout,
method,
w,
nptperyear,
ylu,
iters = 2,
wFUN = wTSM,
verbose = FALSE,
...
)
|
prior |
A vector of initial values for the parameters for which optimal
values are to be found. |
sFUN |
The name of fine curve fitting functions, can be one of |
y |
Numeric vector, vegetation index time-series |
t |
Numeric vector, |
tout |
Corresponding doy of prediction. |
method |
The name of optimization method to solve fine fitting, one of
|
w |
(optional) Numeric vector, weights of |
nptperyear |
Integer, number of images per year, passed to |
ylu |
|
iters |
How many times curve fitting is implemented. |
wFUN |
weights updating function, can be one of 'wTSM', 'wChen' and 'wBisquare'. |
verbose |
Whether to display intermediate variables? |
... |
other parameters passed to |
fFIT object, see fFIT()
for details.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | # library(magrittr)
# library(purrr)
# simulate vegetation time-series
FUN = doubleLog_Beck
par = c( mn = 0.1 , mx = 0.7 , sos = 50 , rsp = 0.1 , eos = 250, rau = 0.1)
par0 = c( mn = 0.15, mx = 0.65, sos = 100, rsp = 0.12, eos = 200, rau = 0.12)
t <- seq(1, 365, 8)
tout <- seq(1, 365, 1)
y <- FUN(par, t)
methods = c("BFGS", "ucminf", "nlm", "nlminb")
opt1 <- I_optim(par0, doubleLog_Beck, y, t, methods) # "BFGS", "ucminf", "nlm",
# opt2 <- I_optimx(prior, fFUN, y, t, tout, )
sFUN = "doubleLog.Beck" # doubleLog.Beck
r <- optim_pheno(par0, sFUN, y, t, tout, method = methods[4],
nptperyear = 46, iters = 2, wFUN = wTSM, verbose = FALSE, use.julia = FALSE)
|
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