Calibration_Michel()
function, which implements the
in-house algorithm of the team. Our algorithm is a mix between a global
method and a local method. The first step of the algorithm is to screen
the parameters space. The second step is a local steepest descent
gradient method. The calibration can be tuned (which parameter not to
calibrate, definition of complex calibration periods, etc.).Param_Sets_GR4J
object. This set of parameters can be
loaded with the following R command: data(Param_Sets_GR4J)
.
The Generalist parameter sets
article explains how to use this list. This set of parameters is quite
general and showed to perform better than automatic calibration when
very few data are available. Good performance is not warranted, but it
is better than nothing. We do not have such a list for the other RR
models.