Set or randomize initial parameter values
m = init(m0)
m = init(m0,R,pars,sp)
m = init(m0) randomizes initial parameter
estimates for model structures m0 for any linear
or nonlinear identified model. It does not support idnlgrey models. m is
the same model structure as m0, but with a different
nominal parameter vector. This vector is used as the initial estimate
by pem.
m = init(m0,R,pars,sp) randomizes parameters
around pars with variances given by the row vector R.
Parameter number k is randomized as pars(k) + e*sqrt(R(k)),
where e is a normal random variable with zero mean
and a variance of 1. The default value of R is
all ones, and the default value of pars is the
nominal parameter vector in m0.
Only models that give stable predictors are accepted. If sp
= 'b', only models that are both stable and have stable
predictors are accepted.
sp = 's' requires stability only of the model,
and sp = 'p' requires stability only of the predictor. sp
= 'p' is the default.
Sufficiently free parameterizations can be stabilized by direct
means without any random search. To just stabilize such an initial
model, set R = 0. With R > 0, randomization is also done.
For model structures where a random search is necessary to find
a stable model/predictor, a maximum of 100 trials is made by init.
It can be difficult to find a stable predictor for high-order systems
by trial and error.