D  R Documentation 
Get derivative of phenofit
object.
D1
first order derivative, D2
second order derivative, n
curvature
curvature.
D1(fit, t = NULL, analytical = FALSE, smoothed.spline = FALSE, ...) D2(fit, t = NULL, analytical = FALSE, smoothed.spline = FALSE, ...) ## S3 method for class 'fFIT' D1(fit, t = NULL, analytical = FALSE, smoothed.spline = FALSE, ...) ## S3 method for class 'fFIT' D2(fit, t = NULL, analytical = FALSE, smoothed.spline = FALSE, ...) curvature(fit, t = NULL, analytical = FALSE, smoothed.spline = FALSE, ...) ## S3 method for class 'fFIT' curvature(fit, t = NULL, analytical = FALSE, smoothed.spline = FALSE, ...)
fit 
A curve fitting object returned by

analytical 
If true, 
smoothed.spline 
Whether apply 
... 
Other parameters will be ignored. 
If fit$fun
has no gradient function or smoothed.spline = TRUE
,
timeseries smoothed by spline first, and get derivatives at last.
If fit$fun
exists and analytical = TRUE
, smoothed.spline
will be ignored.
der1 First order derivative
der2 Second order derivative
k Curvature
# doubleLog.Beck t < seq(1, 365, 8) tout < seq(1, 365, 1) par = c(mn = 0.1, mx = 0.7, sos = 50, rsp = 0.1, eos = 250, rau = 0.1) y < doubleLog.Beck(par, t) methods < c("AG", "Beck", "Elmore", "Gu", "Zhang") # "Klos" too slow fit < curvefit(y, t, tout, methods) x < fit$model$AG d1 < D1(x) d2 < D2(x) d_k < curvature(x)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.