Description Usage Arguments Details Value Examples
Get derivative of phenofit
object.
D1
first order derivative, D2
second order derivative, n
curvature
curvature.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | D1(fit, analytical = TRUE, smoothed.spline = FALSE, ...)
D2(fit, analytical = TRUE, smoothed.spline = FALSE, ...)
## S3 method for class 'fFIT'
D1(fit, analytical = TRUE, smoothed.spline = FALSE, ...)
## S3 method for class 'fFIT'
D2(fit, analytical = TRUE, smoothed.spline = FALSE, ...)
curvature(fit, analytical = TRUE, smoothed.spline = FALSE, ...)
## S3 method for class 'fFIT'
curvature(fit, analytical = TRUE, smoothed.spline = FALSE, ...)
|
fit |
A curve fitting object returned by |
analytical |
If true, |
smoothed.spline |
Whether apply |
... |
Other parameters will be ignored. |
If fit$fun
has no gradient function or smoothed.spline = TRUE
,
time-series smoothed by spline first, and get derivatives at last.
If fit$fun
exists and analytical = TRUE
, smoothed.spline
will be ignored.
der1 First order derivative
der2 Second order derivative
k Curvature
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | library(phenofit)
# simulate vegetation time-series
fFUN = doubleLog.Beck
par = c(
mn = 0.1,
mx = 0.7,
sos = 50,
rsp = 0.1,
eos = 250,
rau = 0.1)
t <- seq(1, 365, 8)
tout <- seq(1, 365, 1)
y <- fFUN(par, t)
methods <- c("AG", "Beck", "Elmore", "Gu", "Zhang") # "Klos" too slow
fFITs <- curvefit(y, t, tout, methods)
fFIT <- fFITs$fFIT$AG
d1 <- D1(fFIT)
d2 <- D2(fFIT)
d_k <- curvature(fFIT)
|
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