invert.lsq.RdPerforms a least-squares inversion of an arbitrary radiative transfer model
(passed as an R function). The inversion attempts to minimize the sum of
residual least squares between modeled and observed spectra via the
Levenberg-Marquardt algorithm (nls.lm function from the minpack.lm
package).
invert.lsq(observed, inits, model, lower = NULL, upper = NULL)
| observed | Vector of observations (e.g. a reflectance spectrum). |
|---|---|
| inits | Vector of initial conditions for the parameters. |
| model | An R function that calls the RTM and returns the error to be minimized. Be sure to include constants here. |
| lower | Lower bounds on parameters (default=NULL, which means -Inf). |
| uppper | Upper bounds on parameters (default=NULL, which means +Inf). |