1. A method comprising: (i) receiving input-output data relating to a characteristic of a system; (ii) establishing with a microprocessor an estimate of at least one hybrid state of a plurality of hybrid states of the system; (iii) establishing with the microprocessor in dependence upon at least the estimate a classification of the input-output data and an identification of a dynamic aspect of the system; (iv) selecting at least one of classification of the input-output data and the identification of the dynamic aspect of the system in dependence upon errors of each with respect to the input-output data; (v) generating a new estimate of the at least one hybrid state of a plurality of hybrid states of the system in dependence upon the selected at least one of classification of the input-output data and the identification of the dynamic aspect of the system; (vi) iterating steps (iii), (iv) and (v) until a predetermined condition is satisfied; (vii) detecting with the microprocessor at least one non-linearity of a plurality of non-linearities in dependence upon at least the input-out data and the selected at least one of classification of the input-output data and the identification of the dynamic aspect of the system; (viii) adjusting a parameter relating to the dynamic aspect of the system determined from the iterative analysis in dependence upon at least the non-linearity of the plurality of non-linearities; and (ix) determining at least one of a static non-linearity parameter of a plurality of static non-linearity linear dynamic parameters and a linear dynamic parameter of a plurality of linear dynamic parameters, wherein; performing an initial analysis comprises at least one of; segmenting at least one subspace of a plurality of subspaces and the corresponding normal for the at least one subspace from the input-output data, each subspace characterized by at least one of a fixed dimension and a variable dimension; and establishing an initial setting for at least one time constant of a plurality of time constants relating to the system, establishing an initial setting for at least one delay constant of a plurality of delay constants relating to the system, and performing at least one of an initial classification of the input-output data and an initial identification of a dynamic aspect of the system.