Goal function of fine curve fitting methods

f_goal(par, fun, y, t, pred, w, ylu, ...)

Arguments

par: A vector of parameters
fun: A curve fitting function, can be one of doubleAG, doubleLog.Beck, doubleLog.Elmore, doubleLog.Gu, doubleLog.Klos, doubleLog.Zhang, see Logistic() for details.
y: Numeric vector, vegetation index time-series
t: Numeric vector, Date variable
pred: Numeric Vector, predicted values
w: (optional) Numeric vector, weights of y. If not specified, weights of all NA values will be wmin, the others will be 1.0.
ylu: [ymin, ymax], which is used to force ypred in the range of ylu.
...: others will be ignored.

Value

RMSE Root Mean Square Error of curve fitting values.

Examples

library(phenofit)

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)

# simulate vegetation time-series
fFUN = doubleLog_Beck
t    <- seq(1, 365, 8)
tout <- seq(1, 365, 1)
y    <- fFUN(par, t)

f_goal(par0, fFUN, y, t)
#> [1] 2.477786