timedist: Fit the Franco model

In nlstimedist: Non-Linear Model Fitting of Time Distribution of Biological Phenomena

Description

Fit the time-course of biological phenomena.

Usage

timedist(data, x, y, r, c, t, ...)

Arguments

data	A data.frame. The data to be included in the model.
x, y	character(1). The x and y values in the data, where the y values are the proportions.
r, c, t	numeric(1). The starting parameters for the model.
...	Additional parameters to be passed to minpack.lm::nlsLM().

Details

The minpack.lm::nlsLM() function is used instead of the stats::nls() function in order to use the Levenberg-Marquardt algorithm which is an extremely robust method of curve-fitting as it is able to switch between Gauss-Newton and gradient descent. This allows it to cope with far-off-optimal starting values. The standard nls function does not use Levenberg-Marquardt; it instead uses the Gauss-Newton type, the PORT routines and a partial linear fit.

See Also

tdPDF(), tdCDF(), tdRSS(), glance(), tdMoments(), tdPercentiles()

Examples

tdTilia <- tdData(tilia, x = "Day", y = "Trees")
model <- timedist(data = tdTilia, x = "Day", y = "propMax", r = 0.1, c = 0.5, t = 120)
model

nlstimedist documentation built on Aug. 27, 2020, 9:07 a.m.