Accelerating the parameters identifiability procedure: Set by set selection

• We are proposing a numerical procedure based on the binary search for accelerating parameters identifiability procedures.
• We applied simultaneous estimation with the identifiability procedures to reduce the dependence on the initial estimates.
• A significant reduction of the computational time was observed when compared with traditional identifiability procedures.

In this paper, a numerical procedure based on the binary search is proposed for accelerating the parameters identifiability procedure. Basically, the parameters are selected set by set using a given criterion for ranking the parameters. Since parameters identifiability procedures are strongly dependent on the initial estimates of parameters values, simultaneous parameters re-estimation step has been proposed in this paper. Two examples were used to evaluate the performance of the proposed criterion. In both cases, a significant reduction of the computational time was observed, and the results regard to the model fit are similar to those criteria based on the selection of parameters one by one, as usually presented in the literature.