FitDoubleLogKlHeavy {phenopix}

Fit a double logistic function to a vector according to Klosterman et al. (2014)

Description

This function fits a double logistic curve to observed values using the function as described in Klosterman et al. (2014), equation 7.

Usage

FitDoubleLogKlHeavy(x, t = index(x), tout = t, max.iter = 200, 
sf=quantile(x, probs=c(0.05, 0.95), na.rm=TRUE), ...)

Arguments

x

A vector or, better, an univariate ts or zoo object.

t

A vector of time (in numeric doys), if not provided index(x) is retrieved.

tout

For gapfilling pourposes, a vector of time steps at which the function can be predicted.

max.iter

Maximum number of iteraction for a single optimization process. See details.

sf

Scaling factors required to normalize the data prior to the fitting. If the function is called by e.g. greenProcess sf is automatically calculated.

...

Further arguments currenlty unused.

Details

The function estimates parameters of the double logistic equation from Klosterman et al. 2014. The wrapper function KlostermanFit calls this function and additionally allows the calculation of uncertainty. So better use KlostermanFit. This function performs an optimization similar in concept to the one performed in FitDoubleLogKlLight but with additional recursive optimization which is about 10 times more time consuming but allows for a better representation of the data. It it suggested to fit the light version of the equation and if the fit is not good enought, check this function out.

Value

A list containing the following items.

predicted

Predicted values from the equation

params

Equation parameters

formula

The equation

Author(s)

Gianluca Filippa <[e-mail]>

References

Klosterman ST, Hufkens K, Gray JM, Melaas E, Sonnentag O, Lavine I, Mitchell L, Norman R, Friedl MA, Richardson A D (2014) Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery, Biogeosciences, 11, 4305-4320, doi:10.5194/bg-11-4305-2014.

See Also

KlostermanFit